CN109064512A - A kind of more calibration point coordinate value detection methods of interactive mode Teaching System - Google Patents
A kind of more calibration point coordinate value detection methods of interactive mode Teaching System Download PDFInfo
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- CN109064512A CN109064512A CN201810852775.XA CN201810852775A CN109064512A CN 109064512 A CN109064512 A CN 109064512A CN 201810852775 A CN201810852775 A CN 201810852775A CN 109064512 A CN109064512 A CN 109064512A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
- G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
- G06F3/0416—Control or interface arrangements specially adapted for digitisers
- G06F3/0418—Control or interface arrangements specially adapted for digitisers for error correction or compensation, e.g. based on parallax, calibration or alignment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
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- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
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Abstract
The invention discloses a kind of more calibration point coordinate value detection methods of interactive Teaching System, are related to coordinate measurement field.The present invention includes the following steps: step S01: sample collection: acquisition present image, background image and mask image；Step S02: image procossing: each pixel of traversal present image, background image and mask image extracts the connected domain of each calibration point in foreground picture；Step S03: obtain calibration point mass center: after judging each connected domain area, the central moment for calculating remaining connected domain obtains the center-of-mass coordinate of each calibration point on foreground image；Step S04: the corresponding coordinate value of calibration point is obtained.The image that the present invention passes through acquisition camera and projector crawl, connected domain is obtained to image procossing, the center-of-mass coordinate of each calibration point is obtained according to connected domain, the corresponding coordinate value of each calibration point is calculated by traversal, slope, sequence scheduling algorithm again, once obtain multiple calibration points, the entire calibration process time is saved, calibration efficiency is improved.
Description
Technical field
The invention belongs to coordinate measurement fields, more particularly to a kind of more calibration point coordinate values of interactive Teaching System
Detection method.
Background technique
Interactive Teaching System is the products such as set computer, projector, camera, infrared transmitter, is realized interactive
Function.Interactive classroom device for projecting is by realizing and operating computer screen in perspective plane finger or infrared stylus touch-control
The method of the same effect of curtain.Wherein, automatic Calibration is exactly the mapping relations calculated between perspective plane and computer screen, to carry out
Mouse events are carried out on operation perspective plane, realize interactive function.During automatic Calibration, need to obtain different on screen
The coordinate value (the corresponding calibration point in each position) of position, calibration point is exactly to draw circle up.
But the detection method in traditional calibration point coordinate value can only detect single calibration point every time, when the multiple seats of needs
When scale value, a calibration point is detected at regular intervals.Such calibration process takes around 1-2 minutes (49 marks of detection
Fixed point), time-consuming long, low efficiency.
Therefore, the corresponding coordinate value of multiple calibration points can once be obtained by being badly in need of one kind, save the entire coordinate of system calibrating
Time.
Summary of the invention
The purpose of the present invention is to provide a kind of more calibration point coordinate value detection methods of interactive Teaching System, pass through
The image for acquiring camera and projector crawl obtains connected domain to image procossing, obtains the matter of each calibration point according to connected domain
Heart coordinate, then the corresponding coordinate value of each calibration point is calculated by traversal, slope, sequence scheduling algorithm, solve existing mark
Fixed point can only detect the problem of time-consuming, low efficiency caused by single calibration point every time.
In order to solve the above technical problems, the present invention is achieved by the following technical solutions:
The present invention is a kind of more calibration point coordinate value detection methods of interactive Teaching System, is included the following steps:
Step S01: sample collection: the sample information of acquisition includes present image, background image and mask image；
Step S02: image procossing: each pixel of traversal present image, background image and mask image, before operation obtains
Jing Tu extracts the connected domain of each calibration point in foreground picture；
Step S03: it obtains calibration point mass center: after judging each connected domain area, excluding area less than threshold value
Connected domain, the central moment for calculating remaining connected domain obtains the center-of-mass coordinate of each calibration point on foreground image, coordinate is put into
In centers container；
Step S04: the corresponding coordinate value of calibration point is obtained；
Wherein, in the step S04, obtaining the corresponding coordinate value of calibration point, specific step is as follows:
Step S041: it traverses the center-of-mass coordinate of calibration point in centers container and the ordinate y of each calibration point is carried out
Sequence；
Step S042: centers [0] basic point information is stored in slopecounts container simultaneously ascending sort, is calculated
The absolute value of slope is stored in slopecompare container between other each calibration points in centers container, obtain at basic point
In other calibration point numbers of same a line；
Step S043: it extracts and is put into same_row container positioned at the calibration point of same a line, remaining calibration point is again
It puts back in centers container；
Traversal is obtained the abscissa and liter of a line calibration point in same_row container by step S044: outermost layer for circulation
Sequence arrangement, then corresponded with the ordinate y of calibration point in centers container in step S041, deposit counts_row two dimension
In container；
Step S045: traversing entire counts_row two-dimensional container, and the abscissa x of each calibration point is put into center_x
The ordinate y of each calibration point is put into center_y array, obtains the coordinate value of corresponding calibration point by array.
Preferably, in the step S01, the present image is the image that camera grabs multiple calibration points；The background
Image is the image that camera removes calibration point；The mask image is projector projects face opereating specification image.
Preferably, in the step S02, extracting connected domain, detailed process is as follows:
Step 1: each pixel of traversal present image, background image and mask image；
Step 2: obtaining poor figure with the pixel value that the pixel value of present image subtracts Background；
Step 3: doing AND operation with the pixel value of the pixel value of poor figure and mask image, obtain foreground picture；
Step 4: extracting the connected domain of each calibration point of foreground picture.
Preferably, in the step S03, the range of threshold value is 4-6；The connected domain that area is less than or equal to threshold value is excluded,
Retention area is greater than the connected domain of threshold value.
Preferably, in the step S042, the calculation formula of slope are as follows:
Slope=abs ((pt1.y-pt2.y)/(pt1.x-pt2.x+0.000001f))；
In formula, slope is ascent, i.e. slope；Abs () is ABS function；Pt1.y-pt2.y, which is that two calibration points are vertical, to be sat
Target difference；Pt1.x-pt2.x is the difference of two calibration point abscissas.
Preferably, it in the step S043, is recycled using the double-deck for, outer layer for loops through slopecompare container
Mileage evidence, internal layer for loops through slopecounts container mileage evidence, and the every traversal of slopecompare container is primary,
Slopecounts container requires to traverse again.
Preferably, the container is a kind of sequence container for encapsulating dynamic size array, various types of right for storing
As.
The invention has the following advantages:
The present invention obtains connected domain to image procossing, according to connected domain by the image of acquisition camera and projector crawl
The center-of-mass coordinate of each calibration point is obtained, then the corresponding coordinate of each calibration point is calculated by traversal, slope, sequence scheduling algorithm
Value, once obtains multiple calibration points, saves the entire calibration process time, improve calibration efficiency.
Certainly, it implements any of the products of the present invention and does not necessarily require achieving all the advantages described above at the same time.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will be described below to embodiment required
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is the more calibration point coordinate value detection method block diagrams of a kind of interactive Teaching System of the invention；
Fig. 2 is the present image of camera acquisition；
Fig. 3 is the mask image of projector acquisition；
Fig. 4 is the structural schematic diagram of image procossing；
Fig. 5 is the schematic illustration for traversing slopecompare container and lopecounts container.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Refering to Figure 1, the present invention is a kind of more calibration point coordinate value detection methods of interactive Teaching System, packet
Include following steps:
Step S01: sample collection: the sample information of acquisition includes present image, background image and mask image；
Step S02: image procossing: each pixel of traversal present image, background image and mask image, before operation obtains
Jing Tu extracts the connected domain of each calibration point in foreground picture；
Step S03: it obtains calibration point mass center: after judging each connected domain area, excluding area less than threshold value
Connected domain, the central moment for calculating remaining connected domain obtains the center-of-mass coordinate of each calibration point on foreground image, coordinate is put into
In vector<Point2d>centers container；
Step S04: the corresponding coordinate value of calibration point is obtained；
Wherein, in step S04, obtaining the corresponding coordinate value of calibration point, specific step is as follows:
Step S041: it traverses the center-of-mass coordinate of calibration point in centers container and the ordinate y of each calibration point is carried out
Sequence, sequence are realized by sort () function；It please refers to shown in Fig. 2, when assert upper left corner calibration point is the first calibration point,
It is followed successively by 1,2,3,4,5,6,7 from left to right, then passes through ascending sort；If assert that lower left corner calibration point is the first calibration point,
It is followed successively by 1,2,3,4,5,6,7 from left to right, then passes through descending sort；If figure and project to the figure on act plate that camera grabs
Corresponding, then the upper left corner is exactly first point, if the figure of camera crawl and the figure projected on act plate differ 180 °, illustrates a left side
Inferior horn is first point；
Step S042: centers [0] basic point information is stored in centor<double>slopecounts container and is risen
Sequence sequence, the absolute value for calculating slope between other each calibration points in centers container are stored in slopecompare container, energy
The cross-interference issue between calibration point every trade is enough distinguished, obtains and is in other calibration point numbers with a line with basic point, it can be with from Fig. 2
It is seen that there is 6 corresponding calibration points and is located at same a line；
Step S043: extracting positioned at the calibration point of same a line and be put into vector<Point2d>same_row container,
Remaining calibration point places back in centers container；
Step S044: outermost layer for circulation, obtains the abscissa of a line calibration point in same_row container for traversal and leads to
The arrangement of sort () function ascending order is crossed, then is corresponded with the ordinate y of calibration point in centers container in step S041, deposit
In counts_row two-dimensional container；
Step S045: traversing entire counts_row two-dimensional container, and the abscissa x of each calibration point is put into center_x
The ordinate y of each calibration point is put into center_y array, obtains the coordinate value of corresponding calibration point by array.
Wherein, in step S01, present image as shown in Figure 2 is the image that camera grabs multiple calibration points；Background image is
Camera removes the image of calibration point；Mask image as shown in Figure 3 is projector projects face opereating specification image.
It please refers to shown in Fig. 4, in step S02, extracting connected domain, detailed process is as follows:
Step 1: each pixel of traversal present image, background image and mask image；
Step 2: obtaining poor figure with the pixel value that the pixel value of present image subtracts Background；
Step 3: doing AND operation with the pixel value of the pixel value of poor figure and mask image, obtain foreground picture, AND operation
It can exclude the interference to calibration point on present image；
Wherein, in step S03, the range of threshold value is 5；The connected domain that area is less than or equal to 5 is excluded, through a step to interference
Point is filtered, and Retention area is greater than the connected domain of threshold value.
Wherein, in step S042, the calculation formula of slope are as follows:
Slope=abs ((pt1.y-pt2.y)/(pt1.x-pt2.x+0.000001f))；
In formula, slope is ascent, i.e. slope；Abs () is ABS function；Pt1.y-pt2.y, which is that two calibration points are vertical, to be sat
Target difference；Pt1.x-pt2.x is the difference of two calibration point abscissas.
It please refers to shown in Fig. 5, in step S043, the every traversal of slopecompare container is primary, and slopecounts container is all
It needs to traverse again；Arrow 1 indicates the traversal direction of slopecounts, and the corresponding calibration point of preceding 6 slopes is located at same a line,
Therefore it needs to be traversed for 6 times；The traversal direction of the expression of arrow 2 slopecompare；It is recycled using the double-deck for, outer layer for circulation time
Slopecompare container mileage evidence is gone through, internal layer for loops through slopecounts container mileage evidence, if slopecompare
Found in container with found in slopecounts container it is equal, then just by this corresponding calibration point put into same_row hold
In device, otherwise just this calibration point is re-applied in centers container.
Wherein, container is a kind of sequence container for encapsulating dynamic size array, for storing various types of objects.
It is worth noting that, included each unit is only drawn according to function logic in the above system embodiment
Point, but be not limited to the above division, as long as corresponding functions can be realized；In addition, each functional unit is specific
Title is also only for convenience of distinguishing each other, the protection scope being not intended to restrict the invention.
In addition, those of ordinary skill in the art will appreciate that realizing all or part of the steps in the various embodiments described above method
It is that relevant hardware can be instructed to complete by program, corresponding program can store to be situated between in a computer-readable storage
In matter.
Present invention disclosed above preferred embodiment is only intended to help to illustrate the present invention.There is no detailed for preferred embodiment
All details are described, are not limited the invention to the specific embodiments described.Obviously, according to the content of this specification,
It can make many modifications and variations.These embodiments are chosen and specifically described to this specification, is in order to better explain the present invention
Principle and practical application, so that skilled artisan be enable to better understand and utilize the present invention.The present invention is only
It is limited by claims and its full scope and equivalent.
Claims (7)
1. a kind of more calibration point coordinate value detection methods of interactive mode Teaching System, which comprises the steps of:
Step S01: sample collection: the sample information of acquisition includes present image, background image and mask image；
Step S02: image procossing: each pixel of traversal present image, background image and mask image, operation obtain prospect
Figure extracts the connected domain of each calibration point in foreground picture；
Step S03: it obtains calibration point mass center: after judging each connected domain area, excluding the company that area is less than threshold value
Logical domain, the central moment for calculating remaining connected domain obtain the center-of-mass coordinate of each calibration point on foreground image, coordinate are put into
In centers container；
Step S04: the corresponding coordinate value of calibration point is obtained；
Wherein, in the step S04, obtaining the corresponding coordinate value of calibration point, specific step is as follows:
Step S041: it traverses the center-of-mass coordinate of calibration point in centers container and the ordinate y of each calibration point is arranged
Sequence；
Step S042: centers [0] basic point information is stored in slopecounts container simultaneously ascending sort, calculates centers
The absolute value of slope is stored in slopecompare container between other each calibration points in container, obtains and is in same a line with basic point
Other calibration point numbers；
Step S043: it extracts and is put into same_row container positioned at the calibration point of same a line, remaining calibration point places back in
In centers container；
Traversal is obtained the abscissa of a line calibration point in same_row container and ascending order is arranged by step S044: outermost layer for circulation
Column, then corresponded with the ordinate y of calibration point in centers container in step S041, it is stored in counts_row two-dimensional container
In；
Step S045: traversing entire counts_row two-dimensional container, and the abscissa x of each calibration point is put into center_x number
The ordinate y of each calibration point is put into center_y array, obtains the coordinate value of corresponding calibration point by group.
2. a kind of more calibration point coordinate value detection methods of interactive Teaching System according to claim 1, feature
It is, in the step S01, the present image is the image that camera grabs multiple calibration points；The background image is camera
Remove the image of calibration point；The mask image is projector projects face opereating specification image.
3. a kind of more calibration point coordinate value detection methods of interactive Teaching System according to claim 1, feature
It is, in the step S02, extracting connected domain, detailed process is as follows:
Step 1: each pixel of traversal present image, background image and mask image；
Step 2: obtaining poor figure with the pixel value that the pixel value of present image subtracts Background；
Step 3: doing AND operation with the pixel value of the pixel value of poor figure and mask image, obtain foreground picture；
Step 4: extracting the connected domain of each calibration point of foreground picture.
4. a kind of more calibration point coordinate value detection methods of interactive Teaching System according to claim 1, feature
It is, in the step S03, the range of threshold value is 4-6；The connected domain that area is less than or equal to threshold value is excluded, Retention area is big
In the connected domain of threshold value.
5. a kind of more calibration point coordinate value detection methods of interactive Teaching System according to claim 1, feature
It is, in the step S042, the calculation formula of slope are as follows:
Slope=abs ((pt1.y-pt2.y)/(pt1.x-pt2.x+0.000001f))；
In formula, slope is ascent, i.e. slope；Abs () is ABS function；Pt1.y-pt2.y is two calibration point ordinates
Difference；Pt1.x-pt2.x is the difference of two calibration point abscissas.
6. a kind of more calibration point coordinate value detection methods of interactive Teaching System according to claim 1, feature
It is, in the step S043, is recycled using the double-deck for, outer layer for loops through slopecompare container mileage evidence, interior
Layer for loops through slopecounts container mileage evidence, and the every traversal of slopecompare container is primary, and slopecounts holds
Device requires to traverse again.
7. the more calibration point coordinate value detection methods of a kind of interactive mode Teaching System described in -6 according to claim 1, special
Sign is that the container is a kind of sequence container for encapsulating dynamic size array, for storing various types of objects.
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| CN104794704A (en) * | 2015-03-27 | 2015-07-22 | 华为技术有限公司 | Calibration template and template detection method, device and terminal |
| US20180137644A1 (en) * | 2016-11-11 | 2018-05-17 | Qualcomm Incorporated | Methods and systems of performing object pose estimation |
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Patent Citations (5)
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| CN102034236A (en) * | 2010-12-01 | 2011-04-27 | 北京航空航天大学 | Multi-camera layered calibration method based on one-dimensional object |
| CN102063718A (en) * | 2010-12-24 | 2011-05-18 | 江南大学 | Field calibration and precision measurement method for spot laser measuring system |
| CN102567989A (en) * | 2011-11-30 | 2012-07-11 | 重庆大学 | Space positioning method based on binocular stereo vision |
| CN104794704A (en) * | 2015-03-27 | 2015-07-22 | 华为技术有限公司 | Calibration template and template detection method, device and terminal |
| US20180137644A1 (en) * | 2016-11-11 | 2018-05-17 | Qualcomm Incorporated | Methods and systems of performing object pose estimation |
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