CN110248159A - One kind being used for food and beverage enterprise's offsite surveillance inspection method - Google Patents
One kind being used for food and beverage enterprise's offsite surveillance inspection method Download PDFInfo
- Publication number
- CN110248159A CN110248159A CN201910496371.6A CN201910496371A CN110248159A CN 110248159 A CN110248159 A CN 110248159A CN 201910496371 A CN201910496371 A CN 201910496371A CN 110248159 A CN110248159 A CN 110248159A
- Authority
- CN
- China
- Prior art keywords
- module
- scanning
- ordinate
- food
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 235000013361 beverage Nutrition 0.000 title claims abstract description 26
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000007689 inspection Methods 0.000 title claims abstract description 9
- 238000012545 processing Methods 0.000 claims abstract description 5
- 238000001514 detection method Methods 0.000 claims description 18
- 238000010276 construction Methods 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000006837 decompression Effects 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 238000007493 shaping process Methods 0.000 claims description 3
- 238000000638 solvent extraction Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 238000010408 sweeping Methods 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 2
- 239000004744 fabric Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- PVCRZXZVBSCCHH-UHFFFAOYSA-N ethyl n-[4-[benzyl(2-phenylethyl)amino]-2-(4-phenoxyphenyl)-1h-imidazo[4,5-c]pyridin-6-yl]carbamate Chemical compound N=1C(NC(=O)OCC)=CC=2NC(C=3C=CC(OC=4C=CC=CC=4)=CC=3)=NC=2C=1N(CC=1C=CC=CC=1)CCC1=CC=CC=C1 PVCRZXZVBSCCHH-UHFFFAOYSA-N 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/12—Hotels or restaurants
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Multimedia (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Signal Processing (AREA)
- Marketing (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
The invention belongs to offsite surveillance technical fields, one kind is disclosed for food and beverage enterprise's offsite surveillance inspection method, food and beverage enterprise's offsite surveillance inspection method that is used for includes: control module, network module, sound module, video module, identification module, barcode scanning module, contrast module and database.The sound module, network module, contrast module and video module pass through circuit line link control module respectively;Database, identification module and barcode scanning module pass through circuit line respectively and connect contrast module.The present invention is capable of the processing site of real time inspection food and beverage enterprise, and whether supervision has violation operation, allows supervisor to carry out remote supervisory, complete function, supervision is effectively.
Description
Technical field
The invention belongs to offsite surveillance technical fields, more particularly to one kind to be used for food and beverage enterprise's offsite surveillance reviewing party
Method.
Background technique
Present people increasingly pay attention to food safety, and the scandal of food and beverage enterprise is often reported in media, and should reinforce to food and drink
The supervision and management of enterprise.But the supervision of present food and beverage enterprise needs someone to arrive food and drink in person by the manpower of superintendent office
Enterprise, it is time-consuming and laborious, and also supervisor is not enough, and supervision is not in place, and efficiency is lower, at high cost.
To sum up, problem of the existing technology is: the supervision of present food and beverage enterprise is needed by the manpower of superintendent office
Someone arrives food and beverage enterprise in person, time-consuming and laborious, and supervisor is not enough, and supervision is not in place, and efficiency is lower, at high cost.
Summary of the invention
In view of the problems of the existing technology, the present invention provides one kind to be used for food and beverage enterprise's offsite surveillance reviewing party
Method.
The invention is realized in this way a kind of check that system includes: for food and beverage enterprise's offsite surveillance
System is checked for food and beverage enterprise's offsite surveillance, which is characterized in that described to be used for food and beverage enterprise's offsite surveillance
Inspection system includes:
Control module is connect with network module, sound module, video module and contrast module, for acquiring to each module
To information handled and judged, determine the information content at the network module supervision of being sent to center;
The normalization Higher Order Cumulants equation group construction method of the time-frequency overlapped signal of the control module includes:
The signal model for receiving signal indicates are as follows:
R (t)=x1(t)+x2(t)+…+xn(t)+v(t)
Wherein, xiIt (t) is each signal component of time-frequency overlapped signal, each component signal is independently uncorrelated, and n is time-frequency weight
The number of folded signal component, θkiIndicate the modulation to each signal component carrier phase, fciFor carrier frequency, AkiBelieve for i-th
Amplitude number at the k moment, TsiFor Baud Length, pi(t) it is raised cosine shaping filter function that rolloff-factor is α, andN (t) is that mean value is 0, variance σ2Stationary white Gaussian noise;
The Higher Order Cumulants formula of mixed signal is as follows:
Both sides are simultaneously divided by the second moment k/2 power of mixed signal:
It is further deformed into:
WhereinWithIndicate the ratio and noise power of each component signal power and general power and the ratio of general power
Value, is expressed asAnd λv;The Higher Order Cumulants of white Gaussian noise are 0, and above formula indicates are as follows:
Building normalizes Higher Order Cumulants equation group as a result:
Network module is connect with control module, for sending the control module content to be sent to supervision center;
The information of circuit-under-test is contained in the frequency domain gated data of the network module, using obtained information, according to
Formula construction compensation factor Fcf(i);Using following formula, compensation factor F is constructedcf(i):
(i=1,2)
G1(i)~G4It (i) is the frequency domain gated data obtained in upper step;
R (i) is ratio factor;
Fcf(i) compensation factor;
Using occlusion compensation formula, the reflection parameters F of error is not coveredS11(i) and configured transmission FS21(i)。
(i=1,2);
Sound module is connect with control module, the sound to be issued for issuing control module;
Video module is connect with control module, for obtaining the video pictures of food and beverage enterprise, and is sent to control module;
The video module carries out rectangle partitioning algorithm to region of variation in a scanning area, and the specific method is as follows:
Step 1, image transmitting terminal obtain the resolution ratio of screen first, what the 0~C of range and row for obtaining column scan were scanned
0~R of range;
The data of current frame image conservation zone are saved in previous frame image buffer area by step 2, transmitting terminal;It intercepts and captures current
Screen bitmaps data and be stored in current frame image buffer area;
Step 3, transmitting terminal initializes variation rectangular area top left co-ordinate first and bottom right angular coordinate is (0,0), next time
Sweep starting point coordinate is (0,0), and row is unchanged to be identified as true, updates the range of column scan and the range of row scanning;
Step 4 judges whether to be expert in scanning range, not exist, jumps to step 10;
Step 5 judges whether within the scope of column scan, does not exist, and jumps to step 8;Within the scope of column scan using every
Column direct comparison method detects current sampling point;Value is different, sets false for the unchanged mark of row first, then sentences
Whether disconnected is the first variation sampled point detected, be using sample point coordinate as the top left co-ordinate for changing rectangular area,
It is not first variation sampled point, the coordinate of the coordinate in the rectangle lower right corner and the point relatively and is maximized as new rectangle
Bottom right angular coordinate, then judge whether the sampled point is first variation sampled point of current row, it is just that the ordinate of the sampled point is same
The ordinate in the rectangle upper left corner is compared and is minimized the top left co-ordinate of more new change rectangular area;It is worth identical, needs
Judge that row is unchanged to identify whether, if it is false, to record starting point of the coordinate as scanning next time for false, detect it is most
Latter column sampled point jumps to step 7 using last column sample point coordinate as the starting point of scanning next time;
Column coordinate is moved to right N column, jumps to step 5 and detect next sampled point by step 6;
Step 7, current row detection finish, and the next time of the next sweep starting point coordinate of current row and lastrow record is scanned
Point coordinate compares, and is maximized as new next sweep starting point coordinate, and line number adds 1, jump to step 4 from next line from
Head starts from left to right to detect;
Step 8, judge to go it is unchanged identify whether as true and variation rectangular area top left co-ordinate is not (0,0), no
It is true, line number adds 1, jumps to step 4;It is true, then shows that full line without different pixels, has obtained the square of a variation
Shape region unit;Obtained variation rectangular area block upper left corner ordinate be moved to the left N column, lower right corner ordinate move right N column
To include image boundary information;
Step 9, records the variation rectangular area coordinate detected and corresponding next sweep starting point coordinate, and judgement is worked as
The range of preceding column scan whether 0~C and row scanning range whether 0~R, be, setting mark show current detection go out variation
Rectangular area mark detects that then line number adds 1 to jump to step 4 to detect next change since next line for the first time
The rectangular area block of change;Until detecting the range beyond row scanning;
Step 10 after this detection, handles next sweep starting point all in this detection, calculates down
The set of secondary scanning range;The ordinate for first next sweep starting point that this is detected is first checked for whether than last column
The ordinate of sampled point is small, is not, which completes, and detects the ordinate of next next sweep starting point;It is, with first
The abscissa in the secondary variation rectangular area upper left corner detected is abscissa, currently to change relevant scanning next time in rectangular area
The ordinate of starting point coordinate is ordinate, generates the top left co-ordinate of a next scanning range;With the change detected for the first time
The abscissa for changing the rectangular area lower right corner is abscissa, generates a scanning next time model by ordinate of the maximum number of column C of screen
The bottom right angular coordinate enclosed;Then handle second next sweep starting point, until next sweep starting point all in this detection all
Until processed;
Step 11 detects scanning area all in next scanning range set, is primarily based on next scanning range collection
The width and height of first scanning area in conjunction, the range of raw row scan and column scan repeat step 3 and examine to step 10
The rectangular area block changed in first scanning area is surveyed, second scanning area is then handled, until next scanning range collection
Until all scanning areas are all detected in conjunction;
Step 12 repeats step 10 to step 11, obtains the variation rectangular area block of scanning range next time, until
The ordinate of all next sweep starting points is greater than or equal to the ordinate of last column sampled point, and entire screen detection finishes;
Step 13 has obtained the smallest not overlapping rectangles of area that all frame images change relative to previous frame image
The set in region, checks the rectangular area in the set, and two rectangle its upper left corner ordinates are identical with lower right corner ordinate, and
The lower right corner abscissa of one rectangle is adjacent with another rectangle upper left corner abscissa, merges into a rectangle, then recompresses
And the set for the sending rectangular area image data that is included and respective coordinates are to client;
Step 14, image receiving end will be based on each rectangular region image data and corresponding seat after received data decompression
Mark is integrated into previous frame image and shows;
Step 15 repeated step 2 every T seconds and arrives step 14, according to difference and the requirements of bandwidth of application scenarios,
It adjusts to interval time T;
Identification module is connect with contrast module, sends comparison to for acquiring the fingerprint of employee, and by finger print information
Module;
Barcode scanning module, connect with contrast module, carries out barcode scanning for the information code to food, and be sent to food information
Food information is stored in database profession by contrast module;
Contrast module is connect with barcode scanning module, identification module, database and control module, for barcode scanning module
The information in information and database being transmitted to identification module compares, and judges institute in processing staff and database
Whether the regulation employee information of storage is consistent, and judges whether food is expired, then transfers data to control module;
Database, for worker's information of store predetermined, the food information that such as finger print information and barcode scanning obtain;
The secure data retrieval method of the database the following steps are included:
Step 1, sensor SiThe data acquisition of a cycle is completed, the data of acquisition are (i, t, { d1, d2..., dn),
Wherein i is sensor number, and t is all issues;SiFirst using AES to data { d1, d2..., dnEncrypted, generate encryption number
According to { (d1)K, (d2)K..., (dn)K, wherein K is data encryption key;
Step 2, SiA undistinguishable Bloom Filter, and each undistinguishable cloth are constructed for each data
Shandong nurse filter distributes a unique ID number, to data dj, SiConstructing a distribution ID number is ijUndistinguishable Broome mistake
Filter Bij;
Step 3, SiEncryption data, corresponding undistinguishable Bloom Filter and its ID number are uploaded into storage section
Point, the data mode of upload are as follows: { (i1, Bi1, (d1)K), (i2, Bi2(d2)K) ..., (in, Bin, (dn)K)};
The undistinguishable Bloom Filter BijBuilding method is as follows:
(1) to BijIt is initialized, to each to 0≤c < m, unit B [c] [H (ij||hk+1(t | | c))] :=0, B
[c][1-H(ij||hk+1(t | | a))] :=1;
(2) h is used1, h2..., hkCalculate h1(dj), h2(dj) ..., hk(dj);Set B [hf(dj)][H(ij||hk+1(t||hf
(dj)))] :=1, B [hf(dj)][1-H(ij||hk+1(t||hf(dj)))] :=0, wherein 1≤f≤k.
The present invention is connect by network module with supervision center, stores effective period of food quality and operator in the database
Fingerprint Identity information, can judge whether food whether there is or not expired, and has illegal personnel to enter food by comparing
Machining area, the processing site of real time inspection food and beverage enterprise is capable of by video module, and whether supervision has violation operation, allow to supervise
It superintends and directs personnel and carries out remote supervisory, complete function, supervision is effectively.
Detailed description of the invention
Fig. 1, Fig. 2 are provided in an embodiment of the present invention for food and beverage enterprise's offsite surveillance inspection system structure diagram;
In figure: 1, control module;2, network module;3, sound module;4, video module;5, identification module;6, it sweeps
Code module;7, contrast module;8, database;9, loudspeaker;10, shell;11, code reader;12, camera;13, finger scan
Device.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, provided in an embodiment of the present invention check that system includes: control mould for food and beverage enterprise's offsite surveillance
Block 1, network module 2, sound module 3, video module 4, identification module 5, barcode scanning module 6, contrast module 7, database 8.
Control module 1 is connect with network module 2, sound module 3, video module 4 and contrast module 7, for each module
Collected information is handled and is judged, determines the information content at 2 supervision of being sent to center of network module.
Network module 2 is connect with control module 1, for sending the content to be sent of control module 1 to supervision center;
Sound module 3 is connect with control module 1, the sound to be issued for issuing control module 1;
Video module 4 is connect with control module 1, for obtaining the video pictures of food and beverage enterprise, and is sent to control module
1;
Identification module 5 is connect with contrast module 7, is sent to pair for acquiring the fingerprint of employee, and by finger print information
Than module 7;
Barcode scanning module 6 is connect with contrast module 7, carries out barcode scanning for the information code to food, and send to food information
To contrast module 7, food information is stored in database 8;
Contrast module 7 is connect with barcode scanning module 6, identification module 5, database 8 and control module 1, for barcode scanning
The information in information and database 8 that module 6 and identification module 5 are transmitted to compares, and judges processing staff and number
Whether it is consistent according to regulation employee information stored in library 8, and judges whether food is expired, then transfers data to
Control module 1;
Database 8, for worker's information of store predetermined, being obtained such as finger print information and 6 barcode scanning of barcode scanning module
Food information.
The normalization Higher Order Cumulants equation group construction method of the time-frequency overlapped signal of the control module includes:
The signal model for receiving signal indicates are as follows:
R (t)=x1(t)+x2(t)+…+xn(t)+v(t)
Wherein, xiIt (t) is each signal component of time-frequency overlapped signal, each component signal is independently uncorrelated, and n is time-frequency weight
The number of folded signal component, θkiIndicate the modulation to each signal component carrier phase, fciFor carrier frequency, AkiBelieve for i-th
Amplitude number at the k moment, TsiFor Baud Length, pi(t) it is raised cosine shaping filter function that rolloff-factor is α, andN (t) is that mean value is 0, variance σ2Stationary white Gaussian noise;
The Higher Order Cumulants formula of mixed signal is as follows:
Both sides are simultaneously divided by the second moment k/2 power of mixed signal:
It is further deformed into:
WhereinWithIndicate the ratio and noise power of each component signal power and general power and the ratio of general power
Value, is expressed asAnd λv;The Higher Order Cumulants of white Gaussian noise are 0, and above formula indicates are as follows:
Building normalizes Higher Order Cumulants equation group as a result:
Network module is connect with control module, for sending the control module content to be sent to supervision center;
The information of circuit-under-test is contained in the frequency domain gated data of the network module, using obtained information, according to
Formula construction compensation factor Fcf(i);Using following formula, compensation factor F is constructedcf(i):
(i=1,2)
G1(i)~G4It (i) is the frequency domain gated data obtained in upper step;
R (i) is ratio factor;
Fcf(i) compensation factor;
Using occlusion compensation formula, the reflection parameters F of error is not coveredS11(i) and configured transmission FS21(i)。
(i=1,2).
The video module carries out rectangle partitioning algorithm to region of variation in a scanning area, and the specific method is as follows:
Step 1, image transmitting terminal obtain the resolution ratio of screen first, what the 0~C of range and row for obtaining column scan were scanned
0~R of range;
The data of current frame image conservation zone are saved in previous frame image buffer area by step 2, transmitting terminal;It intercepts and captures current
Screen bitmaps data and be stored in current frame image buffer area;
Step 3, transmitting terminal initializes variation rectangular area top left co-ordinate first and bottom right angular coordinate is (0,0), next time
Sweep starting point coordinate is (0,0), and row is unchanged to be identified as true, updates the range of column scan and the range of row scanning;
Step 4 judges whether to be expert in scanning range, not exist, jumps to step 10;
Step 5 judges whether within the scope of column scan, does not exist, and jumps to step 8;Within the scope of column scan using every
Column direct comparison method detects current sampling point;Value is different, sets false for the unchanged mark of row first, then sentences
Whether disconnected is the first variation sampled point detected, be using sample point coordinate as the top left co-ordinate for changing rectangular area,
It is not first variation sampled point, the coordinate of the coordinate in the rectangle lower right corner and the point relatively and is maximized as new rectangle
Bottom right angular coordinate, then judge whether the sampled point is first variation sampled point of current row, it is just that the ordinate of the sampled point is same
The ordinate in the rectangle upper left corner is compared and is minimized the top left co-ordinate of more new change rectangular area;It is worth identical, needs
Judge that row is unchanged to identify whether, if it is false, to record starting point of the coordinate as scanning next time for false, detect it is most
Latter column sampled point jumps to step 7 using last column sample point coordinate as the starting point of scanning next time;
Column coordinate is moved to right N column, jumps to step 5 and detect next sampled point by step 6;
Step 7, current row detection finish, and the next time of the next sweep starting point coordinate of current row and lastrow record is scanned
Point coordinate compares, and is maximized as new next sweep starting point coordinate, and line number adds 1, jump to step 4 from next line from
Head starts from left to right to detect;
Step 8, judge to go it is unchanged identify whether as true and variation rectangular area top left co-ordinate is not (0,0), no
It is true, line number adds 1, jumps to step 4;It is true, then shows that full line without different pixels, has obtained the square of a variation
Shape region unit;Obtained variation rectangular area block upper left corner ordinate be moved to the left N column, lower right corner ordinate move right N column
To include image boundary information;
Step 9, records the variation rectangular area coordinate detected and corresponding next sweep starting point coordinate, and judgement is worked as
The range of preceding column scan whether 0~C and row scanning range whether 0~R, be, setting mark show current detection go out variation
Rectangular area mark detects that then line number adds 1 to jump to step 4 to detect next change since next line for the first time
The rectangular area block of change;Until detecting the range beyond row scanning;
Step 10 after this detection, handles next sweep starting point all in this detection, calculates down
The set of secondary scanning range;The ordinate for first next sweep starting point that this is detected is first checked for whether than last column
The ordinate of sampled point is small, is not, which completes, and detects the ordinate of next next sweep starting point;It is, with first
The abscissa in the secondary variation rectangular area upper left corner detected is abscissa, currently to change relevant scanning next time in rectangular area
The ordinate of starting point coordinate is ordinate, generates the top left co-ordinate of a next scanning range;With the change detected for the first time
The abscissa for changing the rectangular area lower right corner is abscissa, generates a scanning next time model by ordinate of the maximum number of column C of screen
The bottom right angular coordinate enclosed;Then handle second next sweep starting point, until next sweep starting point all in this detection all
Until processed;
Step 11 detects scanning area all in next scanning range set, is primarily based on next scanning range collection
The width and height of first scanning area in conjunction, the range of raw row scan and column scan repeat step 3 and examine to step 10
The rectangular area block changed in first scanning area is surveyed, second scanning area is then handled, until next scanning range collection
Until all scanning areas are all detected in conjunction;
Step 12 repeats step 10 to step 11, obtains the variation rectangular area block of scanning range next time, until
The ordinate of all next sweep starting points is greater than or equal to the ordinate of last column sampled point, and entire screen detection finishes;
Step 13 has obtained the smallest not overlapping rectangles of area that all frame images change relative to previous frame image
The set in region, checks the rectangular area in the set, and two rectangle its upper left corner ordinates are identical with lower right corner ordinate, and
The lower right corner abscissa of one rectangle is adjacent with another rectangle upper left corner abscissa, merges into a rectangle, then recompresses
And the set for the sending rectangular area image data that is included and respective coordinates are to client;
Step 14, image receiving end will be based on each rectangular region image data and corresponding seat after received data decompression
Mark is integrated into previous frame image and shows;
Step 15 repeated step 2 every T seconds and arrives step 14, according to difference and the requirements of bandwidth of application scenarios,
It adjusts to interval time T.
The secure data retrieval method of the database the following steps are included:
Step 1, sensor SiThe data acquisition of a cycle is completed, the data of acquisition are (i, t, { d1, d2..., dn),
Wherein i is sensor number, and t is all issues;SiFirst using AES to data { d1, d2..., dnEncrypted, generate encryption number
According to { (d1)K, (d2)K..., (dn)K, wherein K is data encryption key;
Step 2, SiA undistinguishable Bloom Filter, and each undistinguishable cloth are constructed for each data
Shandong nurse filter distributes a unique ID number, to data dj, SiConstructing a distribution ID number is ijUndistinguishable Broome mistake
Filter Bij;
Step 3, SiEncryption data, corresponding undistinguishable Bloom Filter and its ID number are uploaded into storage section
Point, the data mode of upload are as follows: { (i1, Bi1, (d1)K), (i2, Bi2(d2)K) ..., (in, BIn,(dn)K)};
The undistinguishable Bloom Filter BijBuilding method is as follows:
(1) to BijIt is initialized, to each to 0≤c < m, unit B [c] [H (ij||hk+1(t | | c))] :=0, B
[c][1-H(ij||hk+1(t | | a))] :=1;
(2) h is used1, h2..., hkCalculate h1(dj), h2(dj) ..., hk(dj);Set B [hf(dj)][H(ij||hk+1(t||hf
(dj)))] :=1, B [hf(dj)][1-H(ij||hk+1(t||hf(dj)))] :=0, wherein 1≤f≤k.
Loudspeaker 9 is located at the upper left quarter of shell 10, and code reader 11 is located at the lower left quarter of shell 10, and camera 12 is located at shell
10 upper right quarter, fingerprint scanner 13 are located at the right lower quadrant of shell 10.The loudspeaker 9, shell 10, code reader 11, camera
12, fingerprint scanner 13 is all bolted on the surface of shell 10.The sound module 3 is wanted for issuing control module
The sound of sending realizes this function by loudspeaker 9.The video module 4 is used to obtain the video pictures of food and beverage enterprise, and
It is sent to control module, which is then realized by camera 12.The identification module 5 is used to acquire the finger of employee
Line, and send finger print information to contrast module, this function is then carried out by fingerprint scanner 13.The barcode scanning module 6 is used
Barcode scanning is carried out in the information code to food, and contrast module is sent to food information, food information is stored in database profession,
The function is then realized by code reader 11.The device is by barcode scanning module 6, identification module 5, video module 4, sound module
3 functions to be realized all are concentrated on one device, are saved and are taken up space, save the cost, and by multiple functions collection one
Body improves work efficiency.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the invention, belong to
In the range of technical solution of the present invention.
Claims (3)
1. one kind checks system for food and beverage enterprise's offsite surveillance, which is characterized in that described to be used for the non-at-scene prison of food and beverage enterprise
Superintending and directing inspection system includes:
Control module is connect with network module, sound module, video module and contrast module, for collected to each module
Information is handled and is judged, determines the information content at the network module supervision of being sent to center;
The normalization Higher Order Cumulants equation group construction method of the time-frequency overlapped signal of the control module includes:
The signal model for receiving signal indicates are as follows:
R (t)=x1(t)+x2(t)+…+xn(t)+v(t)
Wherein, xiIt (t) is each signal component of time-frequency overlapped signal, each component signal is independently uncorrelated, and n is time-frequency overlapping letter
The number of number component, θkiIndicate the modulation to each signal component carrier phase, fciFor carrier frequency, AkiExist for i-th of signal
The amplitude at k moment, TsiFor Baud Length, pi(t) it is raised cosine shaping filter function that rolloff-factor is α, andN (t) is that mean value is 0, variance σ2Stationary white Gaussian noise;
The Higher Order Cumulants formula of mixed signal is as follows:
Both sides are simultaneously divided by the second moment k/2 power of mixed signal:
It is further deformed into:
WhereinWithIndicate the ratio and noise power of each component signal power and general power and the ratio of general power, point
It is not expressed asAnd λv;The Higher Order Cumulants of white Gaussian noise are 0, and above formula indicates are as follows:
Building normalizes Higher Order Cumulants equation group as a result:
Network module is connect with control module, for sending the control module content to be sent to supervision center;
The information of circuit-under-test is contained in the frequency domain gated data of the network module, using obtained information, according to formula
Construct compensation factor Fcf(i);Using following formula, compensation factor F is constructedcf(i):
(i=1,2)
G1(i)~G4It (i) is the frequency domain gated data obtained in upper step;
R (i) is ratio factor;
Fcf(i) compensation factor;
Using occlusion compensation formula, the reflection parameters F of error is not coveredS11(i) and configured transmission FS21(i);
(i=1,2);
Sound module is connect with control module, the sound to be issued for issuing control module;
Video module is connect with control module, for obtaining the video pictures of food and beverage enterprise, and is sent to control module;
The video module carries out rectangle partitioning algorithm to region of variation in a scanning area, and the specific method is as follows:
Step 1, image transmitting terminal obtain the resolution ratio of screen first, obtain 0~C of range of column scan and the range 0 of row scanning
~R;
The data of current frame image conservation zone are saved in previous frame image buffer area by step 2, transmitting terminal;Intercept and capture current screen
Curtain bitmap data is simultaneously stored in current frame image buffer area;
Step 3, transmitting terminal initializes variation rectangular area top left co-ordinate first and bottom right angular coordinate is (0,0), scanning next time
Starting point coordinate is (0,0), and row is unchanged to be identified as true, updates the range of column scan and the range of row scanning;
Step 4 judges whether to be expert in scanning range, not exist, jumps to step 10;
Step 5 judges whether within the scope of column scan, does not exist, and jumps to step 8;Using straight every column within the scope of column scan
Comparison method is connect to detect current sampling point;Value is different, sets false for the unchanged mark of row first, and then judgement is
No is the first variation sampled point detected, is not to be using sample point coordinate as the top left co-ordinate of variation rectangular area
The coordinate of the coordinate in the rectangle lower right corner and the point relatively and is maximized as new rectangle bottom right by first variation sampled point
Angular coordinate, then judge whether the sampled point is first variation sampled point of current row, it is just by the same rectangle of the ordinate of the sampled point
The ordinate in the upper left corner is compared and is minimized the top left co-ordinate of more new change rectangular area;It is worth identical, needs to judge
Row is unchanged to be identified whether to record starting point of the coordinate as scanning next time if it is false for false, detect it is last
Column sampled point jumps to step 7 using last column sample point coordinate as the starting point of scanning next time;
Column coordinate is moved to right N column, jumps to step 5 and detect next sampled point by step 6;
Step 7, current row detection finish, and the next sweep starting point of the next sweep starting point coordinate of current row and lastrow record is sat
Mark compares, and is maximized as new next sweep starting point coordinate, and line number adds 1, jumps to step 4 and from the beginning opens from next line
Beginning is from left to right detected;
Step 8, judge to go it is unchanged identify whether as true and variation rectangular area top left co-ordinate is not (0,0), be not
True, line number add 1, jump to step 4;It is true, then shows that full line without different pixels, has obtained the rectangle of a variation
Region unit;Obtained variation rectangular area block upper left corner ordinate be moved to the left N column, lower right corner ordinate move right N arrange with
Include image boundary information;
Step 9, records the variation rectangular area coordinate detected and corresponding next sweep starting point coordinate, and forefront is worked as in judgement
The range of scanning whether 0~C and row scanning range whether 0~R, be, setting mark show current detection go out variation rectangle
Area identification is to detect for the first time, and then line number adds 1 to jump to step 4 to detect next variation since next line
Rectangular area block;Until detecting the range beyond row scanning;
Step 10 after this detection, handles next sweep starting point all in this detection, calculates and sweep next time
Retouch the set of range;The ordinate for first next sweep starting point that this is detected is first checked for whether than last column sampling
The ordinate of point is small, is not, which completes, and detects the ordinate of next next sweep starting point;It is, to examine for the first time
The abscissa in the variation rectangular area upper left corner measured is abscissa, currently to change the relevant next sweep starting point in rectangular area
The ordinate of coordinate is ordinate, generates the top left co-ordinate of a next scanning range;With the variation square detected for the first time
The abscissa in the shape region lower right corner is abscissa, generates a next scanning range by ordinate of the maximum number of column C of screen
Bottom right angular coordinate;Then second next sweep starting point is handled, until next sweep starting point all in this detection is all located
Until reason;
Step 11 detects scanning area all in next scanning range set, is primarily based in next scanning range set
The width and height of first scanning area, the range of raw row scan and column scan repeat step 3 to step 10 and detect the
The rectangular area block changed in one scanning area then handles second scanning area, until in next scanning range set
Until all scanning areas are all detected;
Step 12 repeats step 10 to step 11, obtains the variation rectangular area block of scanning range next time, until all
The ordinate of next sweep starting point be greater than or equal to the ordinate of last column sampled point, the detection of entire screen finishes;
Step 13 has obtained the smallest not overlapping rectangles region of area that all frame images change relative to previous frame image
Set, check the rectangular area in the set, two rectangle its upper left corner ordinates are identical with lower right corner ordinate, and one
The lower right corner abscissa of rectangle is adjacent with another rectangle upper left corner abscissa, merges into a rectangle, and then recompression is concurrent
The image data and respective coordinates for sending the set of rectangular area to be included are to client;
Step 14, image receiving end will be based on each rectangular region image data after received data decompression and respective coordinates are whole
It is bonded in previous frame image and shows;
Step 15 repeated step 2 every T seconds to step 14, according to the difference of application scenarios and the requirement of bandwidth, between pair
It adjusts every time T;
Identification module is connect with contrast module, sends comparison mould to for acquiring the fingerprint of employee, and by finger print information
Block;
Barcode scanning module, connect with contrast module, carries out barcode scanning for the information code to food, and be sent to comparison to food information
Food information is stored in database profession by module;
Contrast module is connect with barcode scanning module, identification module, database and control module, for barcode scanning module and body
The information in information and database that part identification module is transmitted to compares, and judges stored in processing staff and database
Regulation employee information whether be consistent, and judge whether food expired, then transfers data to control module;
Database, for worker's information of store predetermined, the food information that such as finger print information and barcode scanning obtain;
The secure data retrieval method of the database the following steps are included:
Step 1, sensor SiThe data acquisition of a cycle is completed, the data of acquisition are (i, t, { d1, d2..., dn), wherein i
For sensor number, t is all issues;SiFirst using AES to data { d1, d2..., dnEncrypted, generate encryption data
{(d1)K, (d2)K..., (dn)K, wherein K is data encryption key;
Step 2, SiA undistinguishable Bloom Filter, and each undistinguishable Broome mistake are constructed for each data
Filter distributes a unique ID number, to data dj, SiConstructing a distribution ID number is ijUndistinguishable Bloom Filter
Bij;
Step 3, SiEncryption data, corresponding undistinguishable Bloom Filter and its ID number are uploaded into memory node, on
The data mode of biography are as follows: { (i1, Bi1, (d1)K), (i2, Bi2(d2)K) ..., (in, BIn,(dn)K)};
The undistinguishable Bloom Filter BijBuilding method is as follows:
(1) to BijIt is initialized, to each to 0≤c < m, unit B [c] [H (ij||hk+1(t | | c))] :=0, B [c]
[1-H(ij||hk+1(t | | a))] :=1;
(2) h is used1, h2..., hkCalculate h1(dj), h2(dj) ..., hk(dj);Set B [hf(dj)][H(ij||hk+1(t||hf
(dj)))] :=1, B [hf(dj)][1-H(ij||hk+1(t||hf(dj)))] :=0, wherein 1≤f≤k.
2. checking system for food and beverage enterprise's offsite surveillance as described in claim 1, which is characterized in that the network module
Supervision center is connected to using internet.
3. checking system for food and beverage enterprise's offsite surveillance as described in claim 1, which is characterized in that loudspeaker is located at shell
The upper left quarter of body, code reader are located at the lower left quarter of shell, and camera is located at the upper right quarter of shell, and fingerprint scanner is located at shell
Right lower quadrant;The loudspeaker, shell, code reader, camera, fingerprint scanner are all bolted on the surface of shell;Institute
Sound module is stated for issuing the control module sound to be issued, is realized by loudspeaker;The video module is for obtaining
The video pictures of food and beverage enterprise, and it is sent to control module, it is realized by camera;The identification module is used for acquisition person
The fingerprint of work, and send finger print information to contrast module, it is carried out by fingerprint scanner;The barcode scanning module is used for food
The information code of product carries out barcode scanning, and is sent to contrast module to food information, food information is stored in database profession, by sweeping
Code device is realized;The function that barcode scanning module, identification module, video module, sound module to be realized all is concentrated on one
On a device.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910496371.6A CN110248159A (en) | 2019-06-10 | 2019-06-10 | One kind being used for food and beverage enterprise's offsite surveillance inspection method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910496371.6A CN110248159A (en) | 2019-06-10 | 2019-06-10 | One kind being used for food and beverage enterprise's offsite surveillance inspection method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN110248159A true CN110248159A (en) | 2019-09-17 |
Family
ID=67886300
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910496371.6A Pending CN110248159A (en) | 2019-06-10 | 2019-06-10 | One kind being used for food and beverage enterprise's offsite surveillance inspection method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110248159A (en) |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1987911A (en) * | 2006-12-28 | 2007-06-27 | 刘忠 | Health safety managing system for catering and public site |
CN103198381A (en) * | 2013-03-28 | 2013-07-10 | 福州天虹电脑科技有限公司 | Off-site supervisory method used for catering enterprises |
CN104735449A (en) * | 2015-02-27 | 2015-06-24 | 成都信息工程学院 | Image transmission method and system based on rectangular segmentation and interlaced scanning |
CN104951812A (en) * | 2014-03-27 | 2015-09-30 | 上海万达全程健康服务有限公司 | Food safety information back-tracing supervision device based on RFID |
CN105978641A (en) * | 2016-04-28 | 2016-09-28 | 西安电子科技大学 | Method for estimating signal-to-noise ratio of time-frequency overlapped signals in cognitive radio |
CN108364381A (en) * | 2018-01-31 | 2018-08-03 | 湖南城市学院 | A kind of intelligence fire behavior escape access control system |
CN108563156A (en) * | 2018-01-09 | 2018-09-21 | 四川文理学院 | A kind of EM equipment module is easy to the interface and expansion interface system of communication |
CN208210159U (en) * | 2018-06-13 | 2018-12-07 | 合肥盈川信息技术有限公司 | A kind of voice-based food safety Regulation equipment |
CN109640025A (en) * | 2018-12-20 | 2019-04-16 | 天津新盛科技有限公司 | A kind of food safety guarantee video-frequency networking supervisory systems |
CN109697685A (en) * | 2018-11-01 | 2019-04-30 | 惠州市格讯信息产业有限公司 | A kind of whole process supervisory systems of canteen food safety |
-
2019
- 2019-06-10 CN CN201910496371.6A patent/CN110248159A/en active Pending
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1987911A (en) * | 2006-12-28 | 2007-06-27 | 刘忠 | Health safety managing system for catering and public site |
CN103198381A (en) * | 2013-03-28 | 2013-07-10 | 福州天虹电脑科技有限公司 | Off-site supervisory method used for catering enterprises |
CN104951812A (en) * | 2014-03-27 | 2015-09-30 | 上海万达全程健康服务有限公司 | Food safety information back-tracing supervision device based on RFID |
CN104735449A (en) * | 2015-02-27 | 2015-06-24 | 成都信息工程学院 | Image transmission method and system based on rectangular segmentation and interlaced scanning |
CN105978641A (en) * | 2016-04-28 | 2016-09-28 | 西安电子科技大学 | Method for estimating signal-to-noise ratio of time-frequency overlapped signals in cognitive radio |
CN108563156A (en) * | 2018-01-09 | 2018-09-21 | 四川文理学院 | A kind of EM equipment module is easy to the interface and expansion interface system of communication |
CN108364381A (en) * | 2018-01-31 | 2018-08-03 | 湖南城市学院 | A kind of intelligence fire behavior escape access control system |
CN208210159U (en) * | 2018-06-13 | 2018-12-07 | 合肥盈川信息技术有限公司 | A kind of voice-based food safety Regulation equipment |
CN109697685A (en) * | 2018-11-01 | 2019-04-30 | 惠州市格讯信息产业有限公司 | A kind of whole process supervisory systems of canteen food safety |
CN109640025A (en) * | 2018-12-20 | 2019-04-16 | 天津新盛科技有限公司 | A kind of food safety guarantee video-frequency networking supervisory systems |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US10121331B1 (en) | Detection of unauthorized devices on ATMs | |
EP0499627B1 (en) | Dynamic method for recognizing objects and image processing system therefor | |
CN103646250B (en) | Pedestrian monitoring method and device based on distance image head and shoulder features | |
CN109446981A (en) | A kind of face's In vivo detection, identity identifying method and device | |
CN101787824B (en) | Intelligent anti-theft lock system | |
CN101443785B (en) | Detecting compositing in a previously conpressed image | |
EP2659668A1 (en) | Calibration device and method for use in a surveillance system for event detection | |
CN106548148A (en) | Method and system for identifying unknown face in video | |
CN109977251A (en) | A method of building identifies commodity based on RGB histogram feature | |
AU2024201525B2 (en) | Gate system, gate apparatus, image processing method therefor, program, and arrangement method for gate apparatus | |
CN107547852A (en) | A kind of big data storage system | |
CN109242119A (en) | A kind of secondary equipment of intelligent converting station automatic detecting method and system | |
DE112019007947T5 (en) | Improved face liveness detection using background/foreground motion analysis | |
CN110111473A (en) | A kind of noninductive quick veritification channel of personnel identity information | |
CN110248159A (en) | One kind being used for food and beverage enterprise's offsite surveillance inspection method | |
CN106407906B (en) | Face face recognition method | |
CN107665328A (en) | Face face recognition method | |
CN106446791A (en) | Smart city public monitoring system | |
JPH09229646A (en) | Object recognition method | |
CN108960459A (en) | It registers login method and device | |
JP2003150963A (en) | Face image recognition method and face image recognition device | |
CN208000588U (en) | A kind of optical scanner pulse wave capture device and a kind of finger-print switch | |
CN111210375A (en) | Multi-functional portable wisdom security protection all-in-one | |
CN219351795U (en) | High-speed shooting instrument for recognizing license | |
CN114973398B (en) | Hierarchical alarm method for view library camera |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190917 |