CN104754324B - Video color bar detecting method and video color bar detecting device - Google Patents
Video color bar detecting method and video color bar detecting device Download PDFInfo
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Abstract
The invention discloses a video color bar detecting method and a video color bar detecting device, wherein the method comprises the following steps: extracting a grey-scale map from a to-be-detected video image; performing grey level histogram calculation on a grey level histogram to generate grey level histogram data; according to the color strip characteristic parameters N, extracting front N elements with biggest element values as special characteristic elements from the grey level histogram data, and performing normalizing calculation on each to-be-determined characteristic element; calculating each normalized special characteristic element and a drop ratio of left and right nearest un-normalized elements; comparing the drop ratio with a threshold value, and determining the characteristic element as the characteristic element when the left and right drop ratio is smaller than the threshold value; judging the quantity of the characteristic elements is equal to the quantity of the color bar characteristic elements, if equal, determining the video image as a color bar image, otherwise, determining that the video image is not a color bar image. According to the invention, the data calculating amount is effectively reduced, the calculating performances are improved and the accurate rate is increased.
Description
Technical field
The invention belongs to field of video image processing, particularly to a kind of video color bar detecting method and device.
Background technology
Visual colour bar provides a kind of directly perceived, efficiently method, to facilitate teletrician to understand system or equipment
The quality condition running.Either in television program designing, broadcast center, or television transmitting station, wire transmission platform, or even
The production of television equipment or maintenance department, the application of colour pattern is all widely.It is true that every morning, in most electricity
Television stations, most programme channel, before formal program broadcasts, all can play the colour pattern of this similar functions, its
Purpose is, (is included broadcast system, transmission/Transmission system and connects come the whole television system of O＆A with this colour pattern
Receive, display system) quality condition so that timely find and solve problem, ready for the broadcast of formal program.
But when formal program broadcasts in this way it is no longer necessary to play colour pattern.It is necessary to right therefore when formal program broadcasts
The video content broadcasting is detected, it is to avoid the broadcast of colour pattern.A lot of video color bar detecting methods are had, wherein in prior art
Template matching and signal colour fidelity is mainly had to analyze two kinds.For template matching mode although it is realized simply, but with template base
Increase also bring the loss in performance.For signal colour fidelity analysis mode although its application flexibly, speed fast, but due to each
All there is different degrees of difference in the colour bar signal that individual source produces on indices, especially through multiple editor, transcoding
Particularly evident afterwards, therefore it is difficult to accurately detect, reduce the accuracy rate of detection.
Content of the invention
The technical problem to be solved in the present invention is, provides a kind of video color bar detecting method and device, is ensureing video
While the accuracy rate of colour bar detection, reduce amount of calculation, improve detection efficiency.
According to an aspect of the present invention, the invention provides a kind of video color bar detecting method, wherein, walk including following
Rapid:
Its gray-scale map is extracted from video image to be detected；
Described gray-scale maps are carried out with grey level histogram calculating, generates intensity histogram diagram data；
According to colour bar characteristic parameter n, from described intensity histogram diagram data, extract front n according to order from big to small
The maximum element of individual element value is as characteristic element undetermined, and carries out Regularization calculating to each characteristic element undetermined；
Calculate the drop ratio of the characteristic element undetermined after each Regularization and its left and right not regular element；
Described drop is compared than with threshold value, when left and right drop is than respectively less than described threshold value, determines this spy undetermined
Levy element and be characterized element；
Judge whether the quantity of described characteristic element is equal with colour bar characteristic parameter, if equal, this video image is
Colour pattern picture, is not otherwise colour pattern picture.
Preferably, in described video color bar detecting method, described gray-scale maps are carried out with grey level histogram calculating, generate
The detailed process of intensity histogram diagram data is as follows:
The pixel value of gray-scale maps is carried out distribution according to 0 to 255 gray level calculate, form a dimension of 0 to 255
Group, the value of each array element is the number of times that this element corresponding grey scale level occurs in gray level image.
Preferably, in described video color bar detecting method, described colour bar characteristic parameter n=8.
Preferably, in described video color bar detecting method, Regularization calculating is carried out to each characteristic element undetermined
Detailed process as follows:
The value of the element of the predetermined quantity adjacent with described characteristic element undetermined is added to described characteristic element value undetermined
On, and the element value being applied is set to 0.
Preferably, in described video color bar detecting method, the predetermined quantity of the described element for superposition is 6.
Preferably, in described video color bar detecting method, calculate the characteristic element undetermined after each Regularization with
During the drop ratio of its left and right not regular element, using equation below calculating drop ratio:
Not regular element value/characteristic element value undetermined=drop ratio recently；
When this characteristic element left side undetermined or the right not regular element, corresponding drop ratio is for 0；
When this determines the characteristic element left side or the right does not have element, corresponding drop ratio is -1.
Preferably, in described video color bar detecting method, for drop than the threshold value being compared be 0.2.
According to a further aspect in the invention, present invention also offers a kind of video color bar detection means, wherein, comprising:
Gray-scale maps extraction module, for extracting gray-scale maps from color video frequency image；
Rectangular histogram generation module, receives the gray-scale maps that described gray-scale maps extraction module sends, and described gray-scale maps are calculated,
Generate intensity histogram diagram data；
Characteristic extracting module, receives described intensity histogram diagram data, and based on described intensity histogram diagram data, successively
Extract through characteristic element undetermined, regular, drop ratio calculating and comparing, obtain characteristic element；
Whether colour bar determining module, using colour bar characteristic parameter and the characteristic element number that obtains, judge this image as color
Bar, and
Data base, for storing various features parameter.
Preferably, in described video color bar detection means, described intensity histogram diagram data is 0 to 255 dimension
Group, the value of each array element is the number of times that this element corresponding grey scale level occurs in gray level image；
Described characteristic extracting module also includes:
Characteristic element extracting sub-module undetermined, from described intensity histogram diagram data, extracts according to order from big to small
Go out the maximum element of front n element value as characteristic element undetermined, wherein n is the colour bar characteristic parameter being stored in data base；
Regular submodule, the value of the element of the predetermined quantity adjacent with described characteristic element undetermined is added to described undetermined
In characteristic element value, and the element value being applied is set to 0；
Drop than calculating sub module, using equation below and condition calculate the characteristic element undetermined after each Regularization with
The drop ratio of its left and right not regular element:
Not regular element value/characteristic element value undetermined=drop ratio recently；
When this characteristic element left or right undetermined not regular element, corresponding drop ratio is for 0；
When this is determined characteristic element left or right and does not have element, corresponding drop is than being -1；
Characteristic element determination sub-module, described drop is compared than with threshold value, when a characteristic element undetermined a left side,
When right drop is than respectively less than described threshold value, determine that this characteristic element undetermined is characterized element.
Be can be seen that just because of by the detection of the colour bar of entire image by the specific embodiments that the invention described above provides
Calculate and be transformed to the colour bar detection of this image grey level histogram is calculated, effectively reduce calculating data volume, greatly improve meter
Calculate performance, simultaneously the constitutive characteristic according to colour pattern picture and colour bar pixel distribution characteristicss on the histogram, using exclusive calculation
Method is amplified, filters, retrieves to colour bar feature, so that the rectangular histogram element data meeting colour bar feature is become apparent from, finally leads to
Cross and calculate these characteristics to determine whether colour bar so that accuracy rate is also higher.
Brief description
By the description to the embodiment of the present invention referring to the drawings, the above-mentioned and other purposes of the present invention, feature and
Advantage will be apparent from, in the accompanying drawings:
Fig. 1 is that the grey level histogram of normal picture is illustrated；
Fig. 2 a is the gray-scale maps of colour pattern picture；
Fig. 2 b is that the grey level histogram of colour pattern picture is illustrated；
The video color bar detecting method flow chart that Fig. 3 provides for the present invention；
The video color bar detection means principle schematic that Fig. 4 provides for the present invention.
Specific embodiment
It is more fully described various embodiments of the present invention hereinafter with reference to accompanying drawing.In various figures, identical element
To be represented using same or similar reference.For the sake of clarity, the various pieces in accompanying drawing are not necessarily to scale.
Fig. 1 illustrates for normal picture grey level histogram, and Fig. 2 a-2b is respectively colour pattern picture and its grey level histogram is illustrated,
Relatively this two schematic diagrams understand, the grey level histogram of colour pattern picture is entirely different with the grey level histogram of normal picture, and
Feature is notable.The present invention utilizes this feature, there is provided a kind of video color bar detecting method and device.
Embodiment one
As shown in figure 3, being video coloured silk field detection method flow chart.Including:
Step s101: receive a width video image from upper layer application, the wide of such as this image is 720 pixels, and height is 576 pictures
Element, extracts the gray-scale maps of this image.
Step s102: grey level histogram calculating is carried out to the gray-scale maps of described image, generates intensity histogram diagram data.Described
Intensity histogram diagram data be a 0-255 one-dimension array.
The calculating of grey level histogram particularly as follows:
The pixel value of gray-scale maps is carried out distribution according to 0 to 255 gray level calculate, form a dimension of 0 to 255
Group, the element in each array includes element value and two parameters of index number, and index number represents this element in gray-scale maps
Corresponding gray level, element value is the number of times that this gray level occurs in gray level image.
The one-dimension array example of grey level histogram is as shown in table 1 below:
Table 1.
In above array: subscript 0-255 represents that the value in square frame is that this gray level exists from 0 to 255 totally 256 gray levels
The number of times occurring in gray level image, what other were unlisted is expressed as 0.For example: in Table 1,0 gray level occurs in that 51840 times, 1
Gray level occurs in that 0 time.
Step s103: from the element of described grey level histogram extracting data quantity n=colour bar characteristic parameter as undetermined
Characteristic element, and Regularization operation is carried out to it.Wherein, colour bar characteristic parameter is to be previously stored in data base, in this reality
Apply in example, colour bar characteristic parameter is set to 8, i.e. n=8.
In the present embodiment, in the intensity histogram diagram data shown in table 1, find out 8 most elements of occurrence number and make
For characteristic element undetermined.The element of 8 maximums is respectively the 0th, 20,38,60,127,150,200,255 grades of element.
Carry out Regularization operation followed by this 8 characteristic elements undetermined.The acting on of Regularization in this step
In strengthening the intensity of these characteristic elements undetermined so as to advantageously in the embodiment of colour bar feature.Specifically, each is undetermined
The value of 6 elements about characteristic element is added on this element, then the value of this 6 elements is set to 0.
About characteristic element undetermined, the selection rule of 6 elements being used for superposition is:
When needing superposition element place gray level to be 0, then need to be 1,2,3,4,5 for the array range of superposition,
6；If when 1, then 0,2,3,4,5,6；If when 2, then 0,1,3,4,5,6；If when 3, then 0,1,2,4,5,6；As
Fruit is when being 255, then 254,253,252,251,250,249；If when 254, then 255,253,252,251,250,249；As
Fruit is when being 253, then 255,254,252,251,250,249；If when 252, then 255,254,253,251,250,249；As
Fruit is other, if representing array element place gray level with x, then in the array of intensity histogram diagram data, needs to use
It is then x-3 in the elemental range being superimposed, x-2, x-1, x+1, x+2, x+3.
According to above rule, carry out regular after obtain array such as table 2 below:
Table 2
| 518400 | ... | 5184020 | ... | 5184038 | ... | 5184060 | ... |
| 51840127 | ... | 51840150 | ... | 51840200 | ... | 51840255 |
Step s104: calculate the drop ratio between selected 8 characteristic elements undetermined and not regular element nearest around,
Computing formula is:
Nearest not regular element value/characteristic element value undetermined=drop ratio.
If the characteristic element left side undetermined or the right do not have element, drop ratio is set to -1, if left or right can not find
Then drop ratio is set to 0 to not regular value element.
As shown in table 2, each characteristic element undetermined can produce two drop ratios, in the present embodiment, due to except this 8
Outside characteristic element undetermined, other elements are 0, therefore except the drop ratio of the 0th grade of element and the 255th grade of right drop ratio are -1
Outward, the drop ratio of remaining element is 0, thus the two-dimensional array of drop ratio is as shown in table 3 below:
Table 3
| Array index | Left drop ratio | Right drop ratio |
| 0 | -1 | 0 |
| 20 | 0 | 0 |
| 38 | 0 | 0 |
| 60 | 0 | 0 |
| 127 | 0 | 0 |
| 150 | 0 | 0 |
| 200 | 0 | 0 |
| 255 | 0 | -1 |
Step s105: successively each characteristic element undetermined is judged, judge its left and right drop than whether less than threshold
Value.If both less than threshold value, judge that this characteristic element undetermined is characterized element in step s106, if being not less than threshold value,
Judge that this characteristic element undetermined is not characteristic element in step s107.In the present embodiment, given threshold is 0.2.If one
Left and right two drop ratios both less than 0.2 of characteristic element undetermined, then assert that this characteristic element undetermined is characterized element.For one
A little special elementses, judge for simplifying, and only judge right drop ratio when array index is 0,1,2, when array index is 255,254,
When 253, only judge left drop ratio.In the present embodiment, left and right two drop ratios of each characteristic element undetermined are both less than
0.2.Therefore can draw, this eight characteristic elements undetermined are all characteristic elements.So, there is the characteristic element prime number of colour bar feature
Measure as 8.
Step s108: colour bar is determined whether according to the quantity that colour bar characteristic parameter represents, when quantity is given more than or equal to this
During fixed quantity, in step s109, judge this width image for colour pattern picture, if the characteristic element quantity obtaining is less than this given
Quantity, in step s110, judge that this width image is not colour pattern picture.In the present embodiment, colour bar characteristic parameter is 8, obtains
Characteristic element be 8, i.e. the quantity of colour bar characteristic parameter=characteristic element, so, show that image in the present embodiment is colour bar
Image.
Embodiment two
Present invention also offers a kind of colour bar detection means, as shown in figure 4, include gray-scale maps extraction module 10, rectangular histogram
Whether generation module 20, characteristic extracting module 30, colour bar determining module 40 database 50, detect video image by this device
There is colour pattern picture.
Gray-scale maps extraction module 10 extracts the gray-scale maps of this image from the video image receiving.Wherein, this video
The wide of image is 720 pixels, and height is 576 pixels.
The gray-scale maps that rectangular histogram generation module 20 obtains to aforementioned gray-scale maps extraction module calculate, and generate intensity histogram
Diagram data.I.e. one-dimension array shown in table 4.
Table 4
| 158400 | 2391 | ... | 1184030 | ... | 5178238 | 80039 | 52040 | ... | 5184059 |
| ... | 5584187 | 5088 | 35089 | 806090 | ... | 9840110 | 760111 | ... | 5330128 |
| 8890129 | 600130 | 50131 | ... | 8900146 | 71840147 | 650148 | ... | 2780198 | 50199 |
| 320200 | 44258201 | ... | 55200230 | 530231 | ... | 0252 | 200253 | 2030254 | 5330255 |
Characteristic extracting module 30 receives described intensity histogram diagram data, and based on described intensity histogram diagram data, according to
Secondary extract through characteristic element undetermined, regular, drop ratio calculating and comparing, obtain characteristic element.
Specifically, characteristic element extracting sub-module 301 undetermined takes out colour bar characteristic parameter 8 from data base 50, as
Foundation, carries out extracting maximum front 8 elements of element value in intensity histogram diagram data, in this enforcements arranges, the respectively the 0th, 30,
38th, 59,87,147,201,230 grades of elements.
Regular submodule 302 carries out regular, that is, on each characteristic element left side undetermined respectively to this 8 characteristic elements undetermined
6 elements of right selection, the value of this 6 elements is added on this element value.The selection of this 6 elements as shown in embodiment one,
Here is not repeated.After regular, table 4 is to be changed into table 5:
Table 5
| 160790 | 01 | ... | 1184030 | ... | 5310238 | 039 | 040 | ... | 5184059 |
| ... | 6430187 | 088 | 089 | 090 | ... | 9840110 | 760111 | ... | 5330128 |
| 8890129 | 600130 | 50131 | ... | 0146 | 81390147 | 0148 | ... | 0198 | 0199 |
| 0200 | 47408201 | ... | 55730230 | 0231 | ... | 0252 | 200253 | 2030254 | 5330255 |
Drop adopts equation below to calculate drop than the feature undetermined calculating after each Regularization than calculating sub module 303
The drop ratio of element and its left and right not regular element:
Not regular element value/characteristic element value undetermined=drop ratio recently；
When this characteristic element undetermined does not have left or right not regular element, corresponding drop is than for 0；
When this is determined characteristic element and does not have left or right element, corresponding drop is than being -1.
Specifically, represent the array element place gray level of intensity histogram diagram data with x, for superposition elemental range then
For x-3, x-2, x-1, x+1, x+2, x+3, therefore, the gray level for calculating left and right two elements of left and right drop ratio is distinguished
For x-4 and x+4.Thus the drop after calculating is than as shown in table 6 below.
Table 6
| Array index | Left drop ratio | Right drop ratio |
| 0 | -1 | 07/160790=0 |
| 30 | 026/1184030=0 | 034/1184030=0 |
| 38 | 034/5310238=0 | 042/5310238=0 |
| 59 | 055/5184059=0 | 063/5184059=0 |
| 87 | 083/6430187=0 | 091/6430187=0 |
| 147 | 0143/81390147=0 | 0151/81390147=0 |
| 201 | 0197/47408201=0 | 0205/47408201=0 |
| 230 | 0226/55730230=0 | 0234/55730230=0 |
Characteristic element determination sub-module 304 according to the drop obtaining in data base than threshold value 0.2, undetermined with each respectively
Two drop ratios of characteristic element compare, and when left and right two drop is than both less than 0.2, just can determine that this characteristic element undetermined
For real characteristic element.In the present embodiment, this 8 characteristic elements undetermined are characteristic element.
The characteristic element obtaining number is compared by colour bar determining module 40 with colour bar characteristic parameter, if the two is equal,
Then judge this image as colour bar.In the present embodiment, colour bar characteristic parameter takes 8, so, the image in the present embodiment is colour pattern
Picture.
According to embodiments of the invention as described above, these embodiments do not have all of details of detailed descriptionthe, not yet
Limit the specific embodiment that this invention is only described.Obviously, as described above, can make many modifications and variations.This explanation
Book is chosen and is specifically described these embodiments, is to preferably explain the principle of the present invention and practical application, so that affiliated
Technical field technical staff can utilize the present invention and modification on the basis of the present invention to use well.The protection model of the present invention
Enclose and should be defined by the scope that the claims in the present invention are defined.
Claims (10)
1. a kind of video color bar detecting method, wherein, comprises the steps:
Its gray-scale map is extracted from video image to be detected；
Described gray-scale maps are carried out with grey level histogram calculating, generates intensity histogram diagram data；
According to colour bar characteristic parameter n, go out the element of front n element value maximum as treating from described grey level histogram extracting data
Determine characteristic element, and Regularization calculating is carried out to each characteristic element undetermined, thus strengthening each special characteristic unit described
The intensity of element, is beneficial to embodiment colour bar feature；
Calculate the drop ratio of the characteristic element undetermined after each Regularization and its left and right not regular recently element；
Described drop is compared than with threshold value, to determine that this characteristic element undetermined is characterized element；
Judge whether the quantity of described characteristic element is equal with colour bar characteristic parameter, if equal, this video image is colour bar
Image, is not otherwise colour pattern picture.
2. described gray-scale maps wherein, are carried out grey level histogram calculating by video color bar detecting method as claimed in claim 1,
The detailed process generating intensity histogram diagram data is as follows:
The pixel value of gray-scale maps is carried out distribution according to 0 to 255 gray level calculate, forms the one-dimension array of 0 to 255,
The value of each array element is the number of times that this element corresponding grey scale level occurs in gray level image.
3. video color bar detecting method as claimed in claim 1, wherein, described colour bar characteristic parameter n=8.
4. video color bar detecting method as claimed in claim 1, wherein, carries out Regularization meter to each characteristic element undetermined
The detailed process calculated is as follows:
The value of the element of the predetermined quantity adjacent with described characteristic element undetermined is added in described characteristic element value undetermined, and
The element value being applied is set to 0.
5. video color bar detecting method as claimed in claim 4, wherein, described predetermined quantity is 6.
6. video color bar detecting method as claimed in claim 1, wherein, calculates the characteristic element undetermined after each Regularization
During with the drop ratio of its left and right not regular element, drop ratio is calculated using equation below:
Not regular element value/characteristic element value undetermined=drop ratio recently,
Wherein, in comparison step, when left and right drop is than respectively less than described threshold value, determine that this characteristic element undetermined is characterized
Element.
7. video color bar detecting method as claimed in claim 6, wherein, when this characteristic element left side undetermined or the right do not have not
During regular element, left drop ratio or right drop are than for 0 accordingly；
When this determines the characteristic element left side or the right does not have element, left drop ratio or right drop ratio are -1 accordingly.
8. video color bar detecting method as claimed in claim 6, wherein, for drop than the threshold value being compared be 0.2.
9. a kind of video color bar detection means, wherein, comprising:
Gray-scale maps extraction module, for extracting gray-scale maps from color video frequency image；
Rectangular histogram generation module, receives the gray-scale maps that described gray-scale maps extraction module sends, and described gray-scale maps are calculated, and generates
Intensity histogram diagram data；
Characteristic extracting module, receives described intensity histogram diagram data, and based on described intensity histogram diagram data, sequentially passes through
Characteristic element undetermined extracts, regular, drop ratio calculating and comparing, and obtains characteristic element；
Colour bar determining module, judges whether the quantity of described characteristic element is equal with colour bar characteristic parameter, if equal, this regards
Frequency image is colour pattern picture, is not otherwise colour pattern picture, and
Data base, for storing various parameters,
Wherein, described characteristic extracting module, according to colour bar characteristic parameter n, goes out front n from described grey level histogram extracting data
The maximum element of element value is as characteristic element undetermined, and carries out Regularization calculating to each characteristic element undetermined, thus increasing
The intensity of each special characteristic element described by force, is beneficial to embodiment colour bar feature；Calculate the spy undetermined after each Regularization
Levy the drop ratio of element and its left and right not regular recently element, described drop is treated with described than for described not regular recently element
Determine the ratio of the element value of characteristic element；Described drop is compared than with threshold value, to determine that this characteristic element undetermined is characterized
Element.
10. video color bar detection means as claimed in claim 9, wherein, described intensity histogram diagram data is the one of 0 to 255
Dimension group, the value of each array element is the number of times that this element corresponding grey scale level occurs in gray level image；
Described characteristic extracting module also includes:
Characteristic element extracting sub-module undetermined, from described intensity histogram diagram data, extracts front n according to order from big to small
As characteristic element undetermined, wherein n is the colour bar characteristic parameter being stored in data base to the maximum element of individual element value；
Regular submodule, the value of the element of the predetermined quantity adjacent with described characteristic element undetermined is added to described feature undetermined
On element value, and the element value being applied is set to 0；
Drop than calculating sub module, using equation below and condition calculate the characteristic element undetermined after each Regularization and its
The drop ratio of left and right not regular element:
Not regular element value/characteristic element value undetermined=drop ratio recently；
When left and right drop is than respectively less than described threshold value, determine that this characteristic element undetermined is characterized element；
When this characteristic element left side undetermined or the right not regular element, corresponding drop ratio is for 0；
When this determines the characteristic element left side or the right does not have element, corresponding drop ratio is -1；
Characteristic element determination sub-module, described drop is compared than with threshold value, when a characteristic element undetermined left and right fall
When difference is than respectively less than described threshold value, determine that this characteristic element undetermined is characterized element.
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