CN105868680A - Channel logo classification method and apparatus - Google Patents
Channel logo classification method and apparatus Download PDFInfo
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- CN105868680A CN105868680A CN201510823533.4A CN201510823533A CN105868680A CN 105868680 A CN105868680 A CN 105868680A CN 201510823533 A CN201510823533 A CN 201510823533A CN 105868680 A CN105868680 A CN 105868680A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/635—Overlay text, e.g. embedded captions in a TV program
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Abstract
The present invention discloses a channel log classification method and apparatus, and relates to the technical field of information identification. The method comprises: acquiring a channel logo region comprising a channel logo; and performing classification on the channel logo according to a length-to-width ratio, a gray level and a color of the channel logo region, so as to obtain a classification result of the channel logo. According to the method and apparatus disclosed by the present invention, an image matching algorithm is not directly adopted any longer, but classification is performed on the channel logo according to the length-to-width ratio, gray level and color of the channel logo region, so as to obtain the classification result of the channel logo, so that identification can be performed by means of the classification result during channel logo identification, which improves matching accuracy and matching efficiency of channel logos.
Description
Technical field
The present invention relates to information discriminating technology field, particularly to a kind of station symbol sorting technique and dress
Put.
Background technology
Along with the impact of the Internet tide, advance TV is towards the trend development of intelligent television.Existing
For TV (the most super TV), comprise a large amount of order video, programme televised live, the most mostly
The TV programme of number remain the station symbol of program product side.Identify that station symbol will effectively realize programme
Function, understands user preferences, it is achieved the input of value-added service.
CCTV's platform have disseminate news, social education, entertainment, the multiple merit such as information service
Can, it is Chinese important ideological and cultural front, is the mainstream media of China Today most competitiveness
One of.CCTV's platform as one of television station most common in advance TV, that viewing rate is high, its
Identifying of station symbol occupies critical positions in overall station symbol technology.The basis of CCTV's platform identification is then
Being to judge certain station symbol whether CCTV's station symbol, design screening rule carries out classification process.
CCTV's platform, satellite TV's platform, local broadcasting stations are not carried out many by existing TV station symbol recognition technology mostly
Sample identification, typically no design CCTV platform sifting sort method, but directly use image
Join algorithm, cause matching accuracy rate and matching efficiency relatively low.For making up the deficiency of existing scheme,
Need a kind of station symbol sorting technique of design.
Summary of the invention
The embodiment of the present invention provides a kind of station symbol sorting technique and device, in order to solve prior art
Middle matching accuracy rate and the relatively low defect of matching efficiency.
The embodiment of the present invention provides a kind of station symbol sorting technique, and described method includes:
Obtain the station symbol region including station symbol；
Described station symbol is classified by length-width ratio, gray scale and color according to described station symbol region,
To obtain the classification results of described station symbol.
The embodiment of the present invention provides a kind of station symbol sorter, and described device includes:
Area acquisition unit, for obtaining the station symbol region including station symbol；
Station symbol taxon, for length-width ratio, gray scale and color pair according to described station symbol region
Described station symbol is classified, to obtain the classification results of described station symbol.
The present invention the most directly uses image matching algorithm, but according to the length and width in station symbol region
Station symbol is classified, to obtain the classification results of station symbol by ratio, gray scale and color, it is possible at platform
When identifying other, it is identified by classification results, improves matching accuracy rate and the coupling of station symbol
Efficiency.
Accompanying drawing explanation
Fig. 1 is the flow chart of the station symbol sorting technique of one embodiment of the present invention；
Fig. 2 is the flow chart of the station symbol sorting technique of one embodiment of the present invention；
The schematic diagram of 5 station symbols of Tu3Shi CCTV；
The schematic diagram of Tu4Shi Chongqing satellite TV station symbol；
The schematic diagram of Tu5Shi BTV station symbol；
Fig. 6 is the gray-scale map of station symbol shown in Fig. 3；
Fig. 7 is the gray-scale map of station symbol shown in Fig. 4；
Fig. 8 is the gray-scale map of station symbol shown in Fig. 5；
Fig. 9 is the schematic diagram of area4～the area7 sub-block to station symbol shown in Fig. 6；
Figure 10 is the schematic diagram of area4～the area7 sub-block to station symbol shown in Fig. 7；
Figure 11 is the schematic diagram of area4～the area7 sub-block to station symbol shown in Fig. 8；
Figure 12 is the structured flowchart of the station symbol sorter of one embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawings and embodiment, the detailed description of the invention of the present invention is made the most in detail
Describe.Following example are used for illustrating the present invention, but are not limited to the scope of the present invention.
Fig. 1 is the flow chart of the station symbol sorting technique of one embodiment of the present invention；With reference to Fig. 1,
Described method includes:
S101: obtain the station symbol region including station symbol；
It should be noted that described station symbol region is and only includes platform target area.
It will be appreciated that described station symbol region can be extracted in several ways, in order to prevent
The impact on TV station symbol recognition of the noise such as random noise, picture noise, in present embodiment, passes through
Following steps acquisition station symbol region:
(1) in the predeterminable area of the video including station symbol, video frame images sequence is obtained；
According to priori, (certainly, station symbol is substantially all is positioned at the upper left corner of video frame images
If being in other positions, it is possible to carry out accommodation as required), therefore station symbol inspection
During survey, only need to extract fixing upper left corner area (i.e. predeterminable area) and detect region as station symbol
?.Prior art obtains station symbol region, this reality generally according to optimal region rule (GSR)
The mode difference from prior art of executing is: (1) calculates all station symbols at each video frame images
In the proportional positions that effectively identifies；(2) maximum magnitude of all proportions position is calculated as station symbol
The region of region segmentation.As a example by the video of 1920*1080, station symbol cut zone is row
Starting position 80 (1/24), arranges starting position 40 (1/27), line width 450 (15/64), col width
180 (1/6), certainly, described proportional positions can the most suitably adjust, this enforcement
This is not any limitation as by mode.
For information unrelated in elimination image, recover or strengthen useful relevant information, improve spy
The detectability levied, simplifies data to greatest extent, to guarantee the reliability identified, this enforcement
In mode, each video frame images can carry out pretreatment, described pretreatment includes: region segmentation,
At least one in gray processing and image enhaucament, certainly, may also include other processing procedures, this
This is not any limitation as by embodiment.
Described pretreatment can use formula Gray=0.33R+0.59G+0.11B to carry out gray processing, when
So, it is possible to substituted by modes such as triple channel mean value method or triple channel maximum value process, wherein,
Gray is the gray value of pixel, and R is the red component of pixel, and G is the green component of pixel, B
Blue component for pixel.
The purpose of described image enhaucament is prominent station symbol region effective information, as icon, word,
Numerals etc., image enhaucament uses the gray scale stretching of 0～255 gray levels, it is also possible to rectangular histogram converts
Method substitutes.
(2) each video frame images is carried out edge extracting；
It will be appreciated that the edge violent part that is variation of image grayscale, edge extracting is station identification
Other key, the integrated degree at edge directly affects TV station symbol recognition result, certainly, edge extracting
Method have a lot, such as Canny, LOG, Sobel, Laplace operator method etc..Comprehensively examine
Consider the requirements such as denoising, edge integrity, edge precision, present embodiment uses Canny
Edge detection method.
In implementing, the parameter of Canny edge detection method is set to: weak edge threshold
50, strong edge threshold 200, certainly, it is possible to the most suitably float, such as, threshold
Value is floated in the range of ± 10.
(3) edge of each video frame images is synthesized；
In implementing, presetting of correspondence can be determined according to the quantity of described video frame images
Whether image threshold, be less than described pre-further according to described each marginal point in the quantity of video frame images
If image threshold judges whether to retain this marginal point.
It is to say, pre-build between the quantity of video frame images and pre-set image threshold value is right
Should be related to, search corresponding relation according to the quantity of described video frame images, to determine the pre-of correspondence
If image threshold, there is each marginal point quantity at video frame images less than described pre-set image
During threshold value, do not retain this marginal point, be optionally greater than in the quantity of video frame images at each marginal point
During described pre-set image threshold value, retain this marginal point.
Illustrate to close the edge of each video frame images with a specific embodiment below
Become, but do not limit protection scope of the present invention: setting the N quantity as video frame images, X is pre-
If image threshold.
As N=6, correspondingly, X=4, say, that only marginal point (bag more than 4
Include 4) video frame images in the presence of just retain, if marginal point (includes 3) below 3
Video frame images in the presence of then give up；
When 6 > N > 3 time, correspondingly, X=3, say, that only marginal point (wraps more than 3
Include 3) video frame images in the presence of just retain, if marginal point (includes 2) below 2
Video frame images in the presence of then give up；
When N≤3, correspondingly, X=N, say, that only marginal point is at all videos
Just retaining in the presence of in two field picture, other situations are all given up.
Certainly, the parameter in described corresponding relation can be adjusted according to the resolution of image, this
This is not any limitation as by embodiment.
All recognition accuracy can be caused shadow due to edge noise, black surround and inessential word etc.
Ringing, for improving recognition accuracy further, the edge that can synthesize is optimized process, this enforcement
In mode, described optimization processes and includes: edge noise is deleted, black surround is removed and inessential word
At least one in deletion.
(4) the minimum external matrix at the edge of synthesis is obtained；
(5) respectively each video frame images is split according to described minimum external matrix, and
The image being partitioned into is synthesized by average weighted mode, to obtain station symbol region.
S102: described station symbol is carried out according to length-width ratio, gray scale and the color in described station symbol region
Classification, to obtain the classification results of described station symbol.
Research finds, CCTV's station symbol finds relative to satellite TV's station symbol, local broadcasting stations' target feature and difference:
(1) length-width ratio difference, the length-width ratio of CCTV's station symbol is (long: vertical direction length；Wide: water
Square to width) generally it is significantly less than other station symbols；(2) cromogram of CCTV's station symbol has extensively
White pixel feature, especially show left side 2/3 at；(3) CCTV's station symbol gray-scale map piecemeal
After, meet the related constraint that gray scale is close between sub-block, such as average, variance etc..
So, can be come institute by the difference of length-width ratio, gray scale and the color in described station symbol region
State station symbol to classify.
Present embodiment the most directly uses image matching algorithm, but according to the length in station symbol region
Station symbol is classified, to obtain the classification results of station symbol by wide ratio, gray scale and color, it is possible to
During TV station symbol recognition, be identified by classification results, improve station symbol matching accuracy rate and
Join efficiency.
Fig. 2 is the flow chart of the station symbol sorting technique of one embodiment of the present invention；With reference to Fig. 1,
Described method includes:
S201: obtain the station symbol region including station symbol；
Step S201 is identical with step S101 of the embodiment shown in Fig. 1, does not repeats them here.
S202: judge whether the length-width ratio in described station symbol region exceedes default length-width ratio, is exceeding
When presetting length-width ratio, the classification results of described station symbol is set to non-CCTV platform；Length is preset exceeding
When width compares, it is judged that whether gray scale and the color in described station symbol region meet pre-conditioned, meeting
Time pre-conditioned, the classification results of described station symbol is set to CCTV's platform；Be unsatisfactory for pre-conditioned
Time, the classification results of described station symbol is set to non-CCTV platform.
It will be appreciated that one of length-width ratio the most direct feature that is station symbol.In described station symbol region
The station symbol such as HNTV, Dragon TV is only left station symbol circular, oval, and length and width are smaller.
The length-width ratio of television station's station symbols such as CCTV's platform (i.e. CCTV) is significantly greater than these satellite TV's platform station symbols
Length-width ratio.Thus, using length-width ratio as coarse sizing condition.The method calculating length-width ratio is:
Calculate length H and width W, length-width ratio ratio=W/H of station symbol region A.
The ratio of CCTV's station symbol passes through below 0.3, so the coarse sizing condition built is:
ratio<0.3.But, satellite TV's platform such as Inner Mongol satellite TV, Chongqing satellite TV, BTV (includes
The local broadcasting stations of this satellite TV) ratio of station symbol all below 0.3, so, can be screened by length-width ratio
After, more again screened by gray scale and color.
When again being screened by gray scale and color, can carry out point according to following Rule of judgment
Class, say, that arrange and following pre-conditioned classify for judge:
(1) red component in first preset range in the upper left corner, described station symbol region and described
The average of the red component in second preset range in the lower right corner, station symbol region is less than presetting redness
Component.
As seen in figures 3-5, it is considered to the satellite TVs such as Chongqing satellite TV, BTV and the district of CCTV's station symbol
Not.It is divided into 5*3 sub-block (certainly, it is possible to by sides such as 6*3 or 4*3 by row * row in station symbol region
Formula carries out piecemeal), extract first sub-block area1 and first sub-block in the lower right corner in the upper left corner
area2.The red distribution in the two region such as CCTV's platform and Chongqing satellite TV, BTV is completely
Different.Figure shown in Fig. 2 is the area image that video frame images intercepts, and CCTV station symbol
Left side ledge is removed at S201.Integrated interference station symbol and the color characteristic of CCTV's station symbol,
The red average of structure condition 1 (i.e. Condition1) area1 and area2 is less than 150.
(2) on the left of described station symbol region, the gray average in the 3rd preset range is grey less than presetting
Angle value.
Consider fault-tolerance and the translucent feature of CCTV's station symbol of Condition1, take sub-block area3.
With 50 pixels of width in station symbol region as standard, take the most left 8 row pixels in station symbol region (i.e.
Wide 4/25) constitute area3.Fig. 6～8 gives the gray level image of Fig. 3～5.Analysis interference station symbol
With CCTV station symbol at the gray difference of area3, build condition 2 (Condition2) area3
Gray average less than 100.
It will be appreciated that triple channel classics synthetic method Gray=0.33R+0.59G+0.11B can be passed through
Obtain gray level image, it is possible to by triple channel maximum value process, triple channel mean value method etc., this
This is not any limitation as by embodiment.
(3) be at least 4 parts by described station symbol region segmentation, the predetermined fraction after segmentation it
Between pixel average absolute difference less than preset absolute difference；
Owing to Condition1 and Condition2 contains only the self information of each sub-block, need to be by about
Bundle extends to the relation between sub-block.Analyze and find, the word in station symbol region, digital pixel master
Rear 1/3 row in station symbol region to be positioned at.To this end, station symbol region is divided into 2*3 according to row * row
Block (certainly, it is possible to carry out piecemeal by modes such as 3*3), takes front 2*2 sub-block and is expressed as
Area4, area5, area6 and area7.In Fig. 9～11, image is divided into by orthogonal lines
Four sub-blocks, it appeared that the pixel average of 4 sub-blocks all has difference.Multisample strictly calculates
Finding, CCTV's station symbol is substantially following condition at these 4 sub-blocks:
The average of condition 3 (Condition3) area4, area5, area6 and area7 is absolutely
To difference less than 100.
(4) variance of the pixel average between the predetermined fraction after segmentation is less than presetting variance.
It is to say, the variance of the pixel average of 4 sub-blocks all has difference, so, CCTV's platform
It is marked at these 4 sub-blocks and meets following condition:
The equal value sequence of condition 4 (Condition4) area4, area5, area6 and area7
Variance less than 1600.
When certain station symbol sample meets above Condition1～Condition4 simultaneously, can be classified
For CCTV's station symbol, otherwise it is categorized as non-CCTV station symbol.When above-mentioned condition judges simultaneously, accuracy rate
The highest, it is demonstrated experimentally that lack any one condition all can improve the error rate of multisample classification.
For method CCTV based on the multisample platform of present embodiment, satellite TV's platform, local broadcasting stations,
Complete the Monte Carlo experiment of classification.Table 1 gives classification accuracy rate and the error rate of station symbol.
Traversal recognition time is shorter and difference little, all at about 2s.
Table 1 shows, classification accuracy rate more than 95%, embody classifying rules high accuracy,
Stability.Analyzing and find, the reason producing sample classification mistake has:
(1) television video size is stretched or compressed, and causes being difficult to obtain completely and not redundancy
Station symbol region.
(2) CCTV's station symbol is translucent, and the video frame images of input (builds in condition sub-block
The sub-block investigated during Conditon1～Conditon4) just contain red background or interference mesh
Mark.
(3) impact of the saturation of video frame images, tone, some condition sub-block is disturbed.
The average recognition time of table 1 typical electrical television stations station symbol
| Television station | " CCTV's station symbol " class probability | " non-CCTV station symbol " class probability |
| CCTV | 98.4% | 1.6% |
| Satellite TV's platform | 4.5% | 95.5% |
| Local broadcasting stations | 3.8% | 96.2% |
For embodiment of the method, in order to be briefly described, therefore it is all expressed as a series of action
Combination, but those skilled in the art should know, and the embodiment of the present invention is not by described
The restriction of sequence of movement, because according to the embodiment of the present invention, some step can use other suitable
Sequence or simultaneously carry out.Secondly, those skilled in the art also should know, is retouched in description
The embodiment stated belongs to preferred embodiment, and the involved action not necessarily present invention implements
Necessary to example.
Figure 12 is the structured flowchart of the station symbol sorter of one embodiment of the present invention；With reference to figure
12, described device includes:
Area acquisition unit 1201, for obtaining the station symbol region including station symbol；
Station symbol taxon 1202, for length-width ratio, gray scale and face according to described station symbol region
Described station symbol is classified by color, to obtain the classification results of described station symbol.
In a kind of alternative embodiment of the present invention, described area acquisition unit, it is further used for
Video frame images sequence is obtained, to each frame of video figure in the predeterminable area of the video including station symbol
As carrying out edge extracting, the edge of each video frame images is synthesized, obtain the edge of synthesis
Minimum external matrix, respectively each video frame images is carried out point according to described minimum external matrix
Cut, and the image being partitioned into is synthesized by average weighted mode, include platform to obtain
Target station symbol region.
In a kind of alternative embodiment of the present invention, described device also includes:
Pretreatment unit, the noise in the edge removing described extraction and inessential word.
In a kind of alternative embodiment of the present invention, described station symbol taxon, it is further used for
Judge whether the length-width ratio in described station symbol region exceedes default length-width ratio, exceeding default length-width ratio
Time, the classification results of described station symbol is set to non-CCTV platform；When exceeding default length-width ratio, sentence
Whether gray scale and the color in disconnected described station symbol region meet pre-conditioned, pre-conditioned meeting
Time, the classification results of described station symbol is set to CCTV's platform；When being unsatisfactory for pre-conditioned, by institute
The classification results stating station symbol is set to non-CCTV platform.
In a kind of alternative embodiment of the present invention, described pre-conditioned include:
Red component in first preset range in the upper left corner, described station symbol region and described station symbol
The average of the red component in second preset range in the lower right corner, region is less than presetting red component；
And/or,
On the left of described station symbol region, the gray average in the 3rd preset range is less than presetting gray value；
And/or,
It is at least 4 parts by described station symbol region segmentation, between the predetermined fraction after segmentation
The absolute difference of pixel average is less than presetting absolute difference；
And/or,
The variance of the pixel average between the predetermined fraction after segmentation is less than presetting variance.
For device embodiment, due to itself and embodiment of the method basic simlarity, so describing
Fairly simple, relevant part sees the part of embodiment of the method and illustrates.
It should be noted that, in all parts of assembly of the invention, to be realized according to it
Function and parts therein have been carried out logical partitioning, but, the present invention is not only restricted to this, can
As required all parts repartitioned or to combine, for example, it is possible to by some portions
Part is combined as single parts, or some parts can be further broken into more sub-portion
Part.
The all parts embodiment of the present invention can realize with hardware, or with at one or many
The software module run on individual processor realizes, or realizes with combinations thereof.This area
It will be appreciated by the skilled person that microprocessor or digital signal processor can be used in practice
(DSP) one of some or all parts in device according to embodiments of the present invention is realized
A little or repertoire.The present invention is also implemented as performing method as described herein
Part or all equipment or device program (such as, computer program and computer journey
Sequence product).The program of such present invention of realization can store on a computer-readable medium,
Or can be to have the form of one or more signal.Such signal can be from the Internet net
Upper download of standing obtains, or provides on carrier signal, or provides with any other form.
The present invention will be described rather than enters the present invention to it should be noted above-described embodiment
Row limits, and those skilled in the art are without departing from the scope of the appended claims
Alternative embodiment can be designed.In the claims, any ginseng between bracket should not will be located in
Examine symbol construction and become limitations on claims.Word " comprises " and does not excludes the presence of the power of not being listed in
Element in profit requirement or step.Word "a" or "an" before being positioned at element is not arranged
Except there is multiple such element.The present invention can be by means of including the hard of some different elements
Part and realizing by means of properly programmed computer.If weighing at the unit listing equipment for drying
During profit requires, several in these devices can be to carry out concrete body by same hardware branch
Existing.Word first, second and third use do not indicate that any order.Can be by these
Word explanation is title.
Above example is only suitable to illustrate the present invention, and not limitation of the present invention, relevant skill
The those of ordinary skill in art field, without departing from the spirit and scope of the present invention, also
Can make a variety of changes and modification, the technical scheme of the most all equivalents falls within the present invention's
Category, the scope of patent protection of the present invention should be defined by the claims.
Claims (10)
1. a station symbol sorting technique, it is characterised in that described method includes:
Obtain the station symbol region including station symbol；
Described station symbol is classified by length-width ratio, gray scale and color according to described station symbol region,
To obtain the classification results of described station symbol.
2. the method for claim 1, it is characterised in that described acquisition station symbol region,
Farther include:
Video frame images sequence is obtained, to each video in the predeterminable area of the video including station symbol
Two field picture carries out edge extracting, is synthesized at the edge of each video frame images, obtains synthesis
The minimum external matrix at edge, enters each video frame images respectively according to described minimum external matrix
Row segmentation, and the image being partitioned into is synthesized by average weighted mode, to obtain bag
Include the station symbol region of station symbol.
3. method as claimed in claim 2, it is characterised in that described according to described station symbol
Before described station symbol is classified by the length-width ratio in region, gray scale and color, described method is also wrapped
Include:
Remove the noise in described station symbol region and inessential word.
4. the method for claim 1, it is characterised in that described according to described station symbol
Described station symbol is classified by the length-width ratio in region, gray scale and color, farther includes:
Judge whether the length-width ratio in described station symbol region exceedes default length-width ratio, preset length exceeding
Wide than time, the classification results of described station symbol is set to non-CCTV platform；
When exceeding default length-width ratio, it is judged that whether gray scale and the color in described station symbol region meet
Pre-conditioned, when meeting pre-conditioned, the classification results of described station symbol is set to CCTV's platform；
When being unsatisfactory for pre-conditioned, the classification results of described station symbol is set to non-CCTV platform.
5. method as claimed in claim 4, it is characterised in that described pre-conditioned include:
Red component in first preset range in the upper left corner, described station symbol region and described station symbol
The average of the red component in second preset range in the lower right corner, region is less than presetting red component；
And/or,
On the left of described station symbol region, the gray average in the 3rd preset range is less than presetting gray value；
And/or,
It is at least 4 parts by described station symbol region segmentation, between the predetermined fraction after segmentation
The absolute difference of pixel average is less than presetting absolute difference；
And/or,
The variance of the pixel average between the predetermined fraction after segmentation is less than presetting variance.
6. a station symbol sorter, it is characterised in that described device includes:
Area acquisition unit, for obtaining the station symbol region including station symbol；
Station symbol taxon, for length-width ratio, gray scale and color pair according to described station symbol region
Described station symbol is classified, to obtain the classification results of described station symbol.
7. device as claimed in claim 6, it is characterised in that described area acquisition unit,
It is further used in the predeterminable area of the video including station symbol obtaining video frame images sequence, right
Each video frame images carries out edge extracting, is synthesized at the edge of each video frame images, obtains
The minimum external matrix at the edge of synthesis, according to described minimum external matrix respectively to each frame of video
Image is split, and is synthesized by average weighted mode by the image being partitioned into, with
Obtain the station symbol region including station symbol.
8. device as claimed in claim 7, it is characterised in that described device also includes:
Pretreatment unit, the noise in the edge removing described extraction and inessential word.
9. device as claimed in claim 6, it is characterised in that described station symbol taxon,
It is further used for judging whether the length-width ratio in described station symbol region exceedes default length-width ratio, is exceeding
When presetting length-width ratio, the classification results of described station symbol is set to non-CCTV platform；Length is preset exceeding
When width compares, it is judged that whether gray scale and the color in described station symbol region meet pre-conditioned, meeting
Time pre-conditioned, the classification results of described station symbol is set to CCTV's platform；Be unsatisfactory for pre-conditioned
Time, the classification results of described station symbol is set to non-CCTV platform.
10. device as claimed in claim 9, it is characterised in that described pre-conditioned include:
Red component in first preset range in the upper left corner, described station symbol region and described station symbol
The average of the red component in second preset range in the lower right corner, region is less than presetting red component；
And/or,
On the left of described station symbol region, the gray average in the 3rd preset range is less than presetting gray value；
And/or,
It is at least 4 parts by described station symbol region segmentation, between the predetermined fraction after segmentation
The absolute difference of pixel average is less than presetting absolute difference；
And/or,
The variance of the pixel average between the predetermined fraction after segmentation is less than presetting variance.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106682670A (en) * | 2016-12-19 | 2017-05-17 | Tcl集团股份有限公司 | Method and system for identifying station caption |
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