CN104751159A - Video color field detecting method and video color field detecting device - Google Patents
Video color field detecting method and video color field detecting device Download PDFInfo
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Abstract
The invention discloses a video color field detecting method and a video color field detecting device, wherein the method comprises the following steps: extracting a grey-scale map from a to-be-detected video image; calculating a grey level histogram of the grey-scale map to generate grey level histogram data; according to the color field characteristic parameters, performing normalizing calculation on the grey level histogram data; according to the normalized grey level histogram data and the color field characteristic parameters, performing characteristic searching; judging whether the video image is a color field according to the searched characteristic. The device comprises a grey-scale map extracting module, a histogram generating module, a characteristic extracting module, a color field determining module and a database. According to the invention, the data calculating amount is effectively reduced, the calculating performances are improved and the accurate rate is relatively high.
Description
Technical field
The invention belongs to field of video image processing, particularly the color field detection method of a kind of video and device.
Background technology
Color field in TV programme, refers generally to entire image and only comprises certain pixel value, be presented as that entire image is the solid-color image of wherein a certain color, and such as: black field refers to that entire image is the image of black, Red Square refers to that entire image is red image.Generally may use such picture frame in program making process, such as: the blue background used by video keying, green background etc.
When formal program broadcasts, so color field picture can not be there is, therefore when formal program broadcasts, need the video content to broadcasting to detect, avoiding the broadcast of color field picture.In prior art, video color field detection method is a lot, is substantially all the method adopting signal colour fidelity to analyze.Although signal colour fidelity analysis mode is flexible, can detect it is the color field of what color, the calculated amount of data is large, so efficiency is very low.
Summary of the invention
The technical problem to be solved in the present invention is, provides the color field detection method of a kind of video and device, while ensureing the accuracy rate that the color field of video is detected, reduces calculated amount, improves detection efficiency.
According to an aspect of the present invention, the invention provides a kind of video color field detection method, wherein, comprise the steps:
Its gray-scale map is extracted from video image to be detected;
Grey level histogram calculating is carried out to described gray-scale map, generates intensity histogram diagram data;
According to color field characteristic parameter, Regularization calculating is carried out to described intensity histogram diagram data;
According to the intensity histogram diagram data after regular and color field characteristic parameter, carry out signature search;
Judge whether this video image is color field according to the characteristic searched.
Preferably, in the detection method of above-mentioned video color field, carry out grey level histogram calculating to described gray-scale map, the detailed process generating intensity histogram diagram data is as follows:
By the pixel value of gray-scale map according to 0 to 255 gray level carry out distribution calculate, form one dimension first 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.
Preferably, in the detection method of above-mentioned video color field, according to color field characteristic parameter, the detailed process of carrying out Regularization calculating to described intensity histogram diagram data is as follows:
Compare the value of each array element of the first array and the size of given parameters value respectively, the array element being greater than given parameters value is formed the second array;
Compare the drop ratio of each element value in the second array and predetermined grey level range interior element value in the first array respectively;
The value of drop within the scope of this than all array elements being less than predetermined value be superimposed together, form the 3rd array, the array element value be applied is set to 0.
Preferably, in the detection method of above-mentioned video color field, described given parameters value is figure image width × figure image height/2-figure image width × figure image height.
Preferably, in the detection method of above-mentioned video color field, described predetermined grey level range is 6.
Preferably, in the detection method of above-mentioned video color field, according to the intensity histogram diagram data after regular and color field characteristic parameter, carry out signature search, comprise the following steps:
Carry out binary conversion treatment to the element of described 3rd array, the array element higher than given threshold values is characteristic, and calculates the accounting of element value relative to entire image pixel of characteristic.
Preferably, in the detection method of above-mentioned video color field, judge whether this video image is that color field is specific as follows according to the characteristic searched:
Whether the quantity judging described characteristic is one, if be one, judges that the accounting of described characteristic is whether in given color field feature threshold range, if, then described image to be detected is color field picture; If the quantity of characteristic is not one, or the accounting of characteristic is not in given color field feature threshold range, then described image to be detected is not color field picture.
Preferably, in the detection method of above-mentioned video color field, when carrying out binary conversion treatment, the scope of described given threshold value is figure image width × figure image height × 0.8-figure image width × figure image height;
When whether the accounting of more described characteristic is in given color field feature threshold range, described color field feature threshold range is 0.99-1.
According to a further aspect in the invention, the invention provides a kind of video for preceding method color field pick-up unit, wherein, comprising:
Gray-scale map extraction module, for extracting gray-scale map from color video frequency image;
Histogram generation module, receives the gray-scale map that described gray-scale map extraction module sends, calculates described gray-scale map, generates intensity histogram diagram data;
Characteristic extracting module, receives described intensity histogram diagram data, and based on described intensity histogram diagram data, successively through regular, binary conversion treatment and signature search, obtains characteristic;
Color field determination module, the characteristic utilizing the color field feature threshold values range parameter in database He obtain, judges this image whether as color field, and
Database, for storing characteristic parameter.
Preferably, in the pick-up unit of aforesaid video color field, described intensity histogram diagram data is one dimension first array of 0 to 255, and 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 comprises:
Regular submodule, compares the element value received in the first array and the given parameters value that obtains from database, the element being greater than given parameters value is formed the second array;
Superposition submodule, compares the drop ratio of each element value in the second array and predetermined grey level range interior element value in the first array respectively; The value of drop within the scope of this than all array elements being less than predetermined value be superimposed together, form the 3rd array, the array element value be applied is set to 0;
Characteristic element search submodule, carry out binary conversion treatment to the element of described 3rd array, the array element higher than given threshold values is characteristic.。
The specific embodiments provided as can be seen from the invention described above, just because of the detection computations that will be transformed to the color field detection computations of entire image this image grey level histogram, effectively reduces the calculated amount of data, significantly improves calculated performance.Simultaneously according to constitutive characteristic and the color field pixel distribution characteristics on the histogram of color field picture, by amplifying color field feature, filter, retrieve, make the histogram element data meeting color field feature more clear, judge whether this image is color field picture, and accuracy rate is also improved a lot finally by these characteristics of calculating.
Accompanying drawing explanation
By referring to the description of accompanying drawing to the embodiment of the present invention, above-mentioned and other objects of the present invention, feature and advantage will be more clear, in the accompanying drawings:
Fig. 1 is the signal of normal picture grey level histogram;
Fig. 2 is the grey level histogram signal of color field picture;
Fig. 3 is video provided by the invention color field detection method process flow diagram;
Fig. 4 is video provided by the invention color field pick-up unit principle schematic.
Embodiment
Hereinafter with reference to accompanying drawing, various embodiment of the present invention is described in more detail.In various figures, identical element adopts same or similar Reference numeral to represent.For the sake of clarity, the various piece in accompanying drawing is not drawn in proportion.
Fig. 1 is the signal of normal picture grey level histogram, and Fig. 2 is the grey level histogram signal of color field picture, and compare these two schematic diagram known, the grey level histogram of color field picture and the grey level histogram of normal picture are completely different on distributing, and feature is remarkable.The present invention make use of this feature just, provides the color field detection method of a kind of video and device.
Embodiment one
As shown in Figure 3, be video color field detection method process flow diagram.Comprise:
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 pixels, extracts the gray-scale map of this image.
Step S102: carry out grey level histogram calculating to the gray-scale map of described image, generates intensity histogram diagram data.Described intensity histogram diagram data is the one-dimension array of a 0-255.
The calculating of grey level histogram is specially:
By the pixel value of gray-scale map according to 0 to 255 gray level carry out distribution calculate, form the one-dimension array of 0 to 255, to show the difference with other arrays following, in this called after first array.In this first array, the element in each array comprises element value and index number two parameters, and index number represents this element gray level corresponding in gray-scale map, and 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.
| 414606 0 | 0 1 | 22 2 | 0 3 | 58 4 | 0 5 | 0 6 | 34 7 | 0 8 | 0 9 | ... | ... | 0 255 |
Such as, in above first array: subscript 0-255 represents that the value in square frame is the number of times that this gray level occurs in gray level image, and: 0 gray level has occurred 414606 times, 1 gray level has occurred 0 time from 0 to 255 totally 256 gray levels.
Step S103: apply color field characteristic parameter and Regularization calculating is carried out to described intensity histogram diagram data.
The effect of the Regularization in this step is the pixel element filtering out high frequency distribution, in order to increase the accuracy of judgement, by strengthening the intensity of these pixel element, makes it advantageously in the embodiment of color field feature.Regularization process is specially:
First in intensity histogram diagram data, according to given parameters, (it is a color field characteristic parameter, represent the number of times that certain pixel element occurs in the images), the element value of each element of relatively above first array and the size of described given parameters value, form the second array by the array element being greater than given parameters value respectively.When the number of times that certain element occurs in piece image is higher than given parameters, this image is likely color field, finds the element meeting the high frequency distribution of this parameter of some.
Wherein, the span of described given parameters value is figure image width × figure image height/2-figure image width × figure image height.As for image 720 × 576, aforementioned given parameters value, between (720 × 576)/2 to 720 × 576, is exactly so between 207360 to 414720.
For above-mentioned table 1, when given parameters is 207360, the second array obtained more afterwards is as shown in table 2 below:
Table 2.
| 414606 0 |
Known with the contrast of table 2 by table 1, after to histogram data Regularization, the number of array element only leaves one.In other embodiments, may be multiple, but quantity will reduce greatly.
Then, in order to strengthen the feature of element, first calculating the drop ratio of this element and predetermined grey level range (as 6 gray levels) interior element value, determining that drop is than the element being less than certain threshold values, the element value of this element value with the element obtained is superposed.Like this, a characteristic element array is obtained.
Such as, given range is set to 6 gray levels, drop is set to 50 than threshold values, in Table 1, by the element value of the element value 414606 of 0 gray level and adjacent 6 gray levels: 22 of the 0, second gray level of the first gray level, 0 of 3rd gray level, 0 of 0, six gray level of the 58, five gray level of the 4th gray level is compared, comparative result is respectively 414606,412584,414606,414548,414606 and 414606, wherein, all comparative results are all greater than drop than threshold values 50, thus do not need to superpose.
Wherein, drop is a changing value than threshold values, artificially can adjust according to factors such as image sizes.
When carrying out drop than calculating, given range is set to 6 gray levels.When calculative second array element place gray level is 0, so in the first array, the array range for superposing is needed to be 1,2,3,4,5,6; If 1 time, then 0,2,3,4,5,6; If 2 time, then 0,1,3,4,5,6; If 3 time, then 0,1,2,4,5,6; If 255 time, then 254,253,252,251,250,249; If 254 time, then 255,253,252,251,250,249; If 253 time, then 255,254,252,251,250,249; If 252 time, then 255,254,253,251,250,249; If the element of other gray levels, representing the second array element place gray level with x, so in the first array, needing the array range for superposing to be then x-3, x-2, x-1, x+1, x+2, x+3.
Step S104: apply color field characteristic parameter, in the regular result of grey level histogram (array namely shown in table 2), search meets the characteristic of color field feature.Be specially:
First binary conversion treatment is utilized to filter out histogram element lower than given threshold values, to the element higher than this threshold values, calculate the accounting of its value relative to entire image pixel, when this ratio is greater than certain threshold values, think that these characteristic element data are color field characteristics.Wherein, the scope of given threshold value described here can from figure image width × figure image height × 0.8 to figure image width × figure image height.In the present embodiment, 720 × 576 × 0.8=331776 is got.
When given threshold value is 331776, by the element in regular for grey level histogram result respectively compared with 331776, get rid of the element that element value is less than 331776, therefore, after two-value process, obtain characteristic array.In the present embodiment, in table 2, only have an element, and its value 414606 is greater than given threshold value is 331776.Therefore, this element is characteristic.
Next, apply color field characteristic parameter and search color field characteristic out, judge whether this image is color field picture.
Step S105: judge to search for out the quantity of characteristic element whether equal one, if be not equal to, then determine that this image is not color field picture in step S109.
If the quantity of characteristic element equals one, in step S106, calculate the accounting of this element, i.e. characteristic element value/figure image width × figure image height.In the present embodiment, accounting is 414606/720 × 576 ≈ 0.9997.
Step S107, judges whether accounting is greater than 0.99, if be greater than 0.99, then determines that this image is color field picture in step S108.If be not more than 0.99, be namely less than 0.99, then determine that this image is not color field picture in step S109.
In the present embodiment, only have a characteristic element, and its accounting is about 0.9997, is greater than 0.99, thus can judges that this image is color field picture.
By said method, by being transformed to the detection computations to this image grey level histogram to the color field detection computations of entire image, effectively reducing calculating data volume, thus significantly improve calculated performance.The present invention is simultaneously according to constitutive characteristic and these color field pixels distribution characteristics on the histogram of color field picture, by amplifying color field feature, filter, retrieve, make the histogram element data meeting color field feature more clear, determine whether color field finally by these characteristics of calculating, make accuracy rate also corresponding raising.
Embodiment two
Present invention also offers a kind of color field pick-up unit, as shown in Figure 4, comprising: gray-scale map extraction module 10, histogram generation module 20, characteristic extracting module 30, color field determination module 40 and database 50.Detect video image by this device and whether there is color field picture.
Gray-scale map extraction module 10 extracts the gray-scale map of this image from the video image received.Wherein, the wide of this video image is 1920 pixels, and height is 1080 pixels.
Histogram generation module 20 calculates the gray-scale map that aforementioned gray-scale map extraction module obtains, and generates intensity histogram diagram data.Namely the first array shown in table 3.
Table 3:
| 0 0 | ... | 0 122 | 1078000 123 | 990300 124 | 0 125 | 5300 126 | 0 127 | 0 8 | ... | 0 255 |
Characteristic extracting module 30 also comprises regular submodule 301, superposition submodule 302 and characteristic element search submodule 303.After histogram generation module 20 generates intensity histogram diagram data, first, regular submodule 301 pairs of intensity histogram diagram datas carry out Regularization calculating, and detailed process is as follows.
Regular submodule 301 gets a given parameters from database 50, and the size according to image is set as 1920 × 1080/2=1036800.The element value of the first array in table 3 and this value are compared.By comparing, only having the element value of the 123rd gray level to be greater than this setup parameter, thus obtaining the second array, i.e. table 4.
Table 4:
| 1078000 123 |
Superposition submodule 302, according to the element in table 4, calculates the drop ratio of 6 elements near it.Carrying out the method for drop than the element calculated according to what provide in embodiment one for determining, namely representing the second array element place gray level with x, needing the array range for superposing to be then x-3, x-2, x-1, x+1, x+2, x+3.In the present embodiment, x=123, so needing to carry out drop than the element calculated is 120 grades, 121 grades, 122 grades, 124 grades, 125 grades and 126 grades.When the element value of the 123rd grade and the element value of these gray levels are compared, obtain respectively: 1078000,1078000,1078000,87700,1078000,1072700.
Superposition submodule 302 takes out drop than threshold value 200000 (it is the value artificially set according to the size of image) from database 50, and above-mentioned numerical value and drop is compared than threshold value 200000.By comparing, only have the comparative result of 124 grades to be less than this threshold value, therefore, be added to by this grade of element value 123 grades, obtain the 3rd array, namely table 3 becomes table 5:
Table 5:
| 0 0 | ... | 0 122 | 2068300 123 | 0 124 | 0 125 | 5300 126 | 0 127 | 0 8 | ... | 0 255 |
Table 4 becomes table 6:
Table 6:
| 2068300 123 |
When obtaining the 3rd array, namely after table 6, the element in table 6 and binary-state threshold compare by characteristic element search module 303, and binary-state threshold is figure image width × figure image height × 0.8=1920 × 1080 × 0.8=1658880.In the present embodiment, obvious 2068300 are greater than 1658880, thus determine that this element is characteristic element.
The characteristic element that color field determination module 40 is obtained by judging characteristic element search module 303 usually determines whether this image is color field picture.
Whether the number first determining characteristic element is one.When for one, then calculate the accounting of this element.In the present embodiment, only have an element in table 6, its accounting is 2068300/2073600 ≈ 0.9974.This accounting is greater than 0.99, therefore, determines that this image is color field.
Embodiment three
In the present embodiment, take the device shown in embodiment two and the method shown in embodiment one, video image is detected.Owing to being described in detail described device and method in embodiment one and two, in the present embodiment simplified illustration.
The wide of video image is 704 pixels, and height is 576 pixels.First extract the gray-scale map of this image, then carry out histogram calculation.Obtain one-dimension array as shown in table 7:
Table 7:
| 12100 0 | 8020 1 | 20000 2 | 0 3 | 16050 4 | 4200 5 | 160240 6 | ... | 82200 255 |
Then above element value and given parameters 704 × 576/2=202752 are compared, be greater than this given parameters without any an element value, therefore, there is no qualified element.Owing to can not find qualified element, do not need to carry out drop than calculating, without the need to the calculating of binary conversion treatment and accounting yet.Owing to not equaling the element of 1, so can determine that this image is not color field picture.
According to embodiments of the invention as described above, these embodiments do not have all details of detailed descriptionthe, do not limit the specific embodiment that this invention is only described yet.Obviously, according to above description, can make many modifications and variations.This instructions is chosen and is specifically described these embodiments, is to explain principle of the present invention and practical application better, thus makes art technician that the present invention and the amendment on basis of the present invention can be utilized well to use.The scope that protection scope of the present invention should define with the claims in the present invention is as the criterion.
Claims (10)
1. a video color field detection method, wherein, comprises the steps:
Its gray-scale map is extracted from video image to be detected;
Grey level histogram calculating is carried out to described gray-scale map, generates intensity histogram diagram data;
According to color field characteristic parameter, Regularization calculating is carried out to described intensity histogram diagram data;
According to the intensity histogram diagram data after regular and color field characteristic parameter, carry out signature search;
Judge whether this video image is color field according to the characteristic searched.
2. the color field of video as claimed in claim 1 detection method, wherein, carry out grey level histogram calculating to described gray-scale map, the detailed process generating intensity histogram diagram data is as follows:
By the pixel value of gray-scale map according to 0 to 255 gray level carry out distribution calculate, form one dimension first 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. the color field of video as claimed in claim 2 detection method, wherein, according to color field characteristic parameter, the process of carrying out Regularization calculating to described intensity histogram diagram data is specific as follows:
Compare the value of each array element of the first array and the size of given parameters value respectively, the array element being greater than given parameters value is formed the second array;
Compare the drop ratio of each element value in the second array and predetermined grey level range interior element value in the first array respectively;
The value of drop within the scope of this than all array elements being less than predetermined value be superimposed together, form the 3rd array, the array element value be applied is set to 0.
4. the color field of video as claimed in claim 3 detection method, wherein, described given parameters value is figure image width × figure image height/2-figure image width × figure image height.
5. the color field of video as claimed in claim 3 detection method, wherein, described predetermined grey level range is 6.
6. video as claimed in claim 3 color field detection method, wherein, according to the intensity histogram diagram data after regular and color field characteristic parameter, carry out signature search, comprise the following steps:
Carry out binary conversion treatment to the element of described 3rd array, the array element higher than given threshold values is characteristic, and calculates the accounting of element value relative to entire image pixel of characteristic.
7. according to the characteristic searched, the color field of video as claimed in claim 6 detection method, wherein, judges whether this video image is that color field is specific as follows:
Judge quantity and the accounting of described characteristic, if quantity is one, and accounting is in given color field feature threshold range, and described image to be detected is color field picture; If the quantity of characteristic is not one, or the accounting of characteristic is not in given color field feature threshold range, then described image to be detected is not color field picture.
8. the color field of video as claimed in claim 6 detection method, wherein, when carrying out binary conversion treatment, the scope of described given threshold value is figure image width × figure image height × 0.8-figure image width × figure image height;
When whether the accounting of more described characteristic is in given color field feature threshold range, described color field feature threshold range is 0.99-1.
9., for realizing a video color field pick-up unit for the arbitrary described method of claim 1-8, wherein, comprising:
Gray-scale map extraction module, for extracting gray-scale map from color video frequency image;
Histogram generation module, receives the gray-scale map that described gray-scale map extraction module sends, calculates described gray-scale map, generates intensity histogram diagram data;
Characteristic extracting module, receives described intensity histogram diagram data, and based on described intensity histogram diagram data, successively through regular, binary conversion treatment and signature search, obtains characteristic;
Color field determination module, the characteristic utilizing the color field feature threshold values range parameter in database He obtain, judges this image whether as color field picture, and
Database, for storing characteristic parameter.
10. the color field of video as claimed in claim 9 pick-up unit, wherein, described intensity histogram diagram data is one dimension first array of 0 to 255, and 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 comprises:
Regular submodule, compares the element value received in the first array and the given parameters value that obtains from database, the element being greater than given parameters value is formed the second array;
Superposition submodule, compares the drop ratio of each element value in the second array and predetermined grey level range interior element value in the first array respectively; The value of drop within the scope of this than all array elements being less than predetermined value be superimposed together, form the 3rd array, the array element value be applied is set to 0;
Characteristic element search submodule, carry out binary conversion treatment to the element of described 3rd array, the array element higher than given threshold values is characteristic.
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