CN103295217B - Pictorial information disposal route and device - Google Patents
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- CN103295217B CN103295217B CN201210052031.2A CN201210052031A CN103295217B CN 103295217 B CN103295217 B CN 103295217B CN 201210052031 A CN201210052031 A CN 201210052031A CN 103295217 B CN103295217 B CN 103295217B
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Abstract
This application discloses a kind of pictorial information disposal route and device, the method comprises: by the first picture to be detected of receiving according to after setting ratio convergent-divergent, and the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size; Choose the sub-pictures in the Similar content region of the second picture to be detected and described reference picture, as sub-pictures to be detected with reference to sub-pictures; By the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determine the similarity of each sub-pictures to be detected and corresponding reference sub-pictures; According to the similarity determined, determine the similarity of the second picture to be detected and reference picture; When the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, store the first picture to be detected received.The method is applicable to most of picture to be detected and detection efficiency is higher.
Description
Technical field
The application relates to computer information technology field, espespecially a kind of pictorial information disposal route and device.
Background technology
Along with the development of network technology, uploading pictures becomes a kind of fashion.A lot of picture uploading system is had to allow user to upload specific picture, also have some can automatic uploading pictures, such as, sectional drawing, state service chart etc. in game, and filter for the detection of uploading pictures can only by manually carrying out, this detection mode takes time and effort, and efficiency is very low.
Detecting the efficiency of uploading pictures to improve, often adopting pixel inspection technique, whether the method needs the pixel of some coordinate judging picture to be detected and reference picture one by one completely the same, and has strict requirement for the size of picture to be detected and quality.Because the method detects picture to be detected based on coordinate, if the size of picture to be detected and reference picture is different, so the coordinate of respective pixel point is just different, and the testing result obtained like this is exactly mistake; In addition, in order to reduce picture file size, a lot of picture can be compressed when uploading, and the picture pixels after compression can change, and also there will be mistake, correctly cannot detect picture when adopting pixel inspection technique to detect picture.Although the efficiency of the method is higher than the mode of hand inspection, the method has strict demand to the size of picture to be detected and quality, and is not suitable for and detects most picture to be detected; And owing to needing the pixel in picture to be detected and the pixel in reference picture to compare one by one, this just causes detection efficiency still very low.Therefore, lack in prior art and can be applicable to most of picture to be detected and the higher detection method of detection efficiency.
Summary of the invention
The embodiment of the present application provides a kind of pictorial information disposal route and device, is applicable to most of picture to be detected and the problem of the higher detection method of detection efficiency in order to solve lacking of existing in prior art.
A kind of pictorial information disposal route, comprising:
By the first picture to be detected of receiving according to after setting ratio convergent-divergent, the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size;
Choose the sub-pictures in the Similar content region of the second picture to be detected and described reference picture, as sub-pictures to be detected with reference to sub-pictures;
By the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determine the similarity of each sub-pictures to be detected and corresponding reference sub-pictures;
According to the similarity determined, determine the similarity of the second picture to be detected and reference picture;
When the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, store the first picture to be detected received.
A kind of pictorial information treating apparatus, comprising:
Picture cutting unit, for receiving first picture to be detected is according to after setting ratio convergent-divergent, and the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size;
Sub-pictures chooses unit, for choosing the sub-pictures in the Similar content region of the second picture to be detected and described reference picture, as sub-pictures to be detected with reference to sub-pictures;
Sub-pictures similarity determining unit, for by the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determines the similarity of each sub-pictures to be detected and corresponding reference sub-pictures;
Picture analogies degree determining unit, for according to the similarity determined, determines the similarity of the second picture to be detected and reference picture;
Image store, for when the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, stores the first picture to be detected received.
The pictorial information disposal route that the embodiment of the present application provides and device, the program is by the first picture to be detected of receiving according to after setting ratio convergent-divergent, and the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size; Choose the sub-pictures in the Similar content region of the second picture to be detected and reference picture, as sub-pictures to be detected with reference to sub-pictures; By the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determine the similarity of each sub-pictures to be detected and corresponding reference sub-pictures; According to the similarity determined, determine the similarity of the second picture to be detected and reference picture; When the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, store the first picture to be detected received.The program, by carrying out gray proces to the sub-pictures to be detected chosen with reference to sub-pictures, just greatly can be got rid of the interference of color, be no longer dependent on the color of picture to be detected, this provides for improved the accuracy of judgement; By determining to reference to whether sub-pictures is similar, sub-pictures to be detected determines whether that whether picture to be detected is similar to reference picture, thus determine whether to store the picture to be detected received.Because the party is for the size of picture to be detected and the specific requirement of quality, therefore go for most of picture to be detected.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide further understanding of the present application, and form a application's part, the schematic description and description of the application, for explaining the application, does not form the improper restriction to the application.In the accompanying drawings:
Fig. 1 is the process flow diagram of pictorial information disposal route in the embodiment of the present application;
Fig. 2 is the schematic diagram of the reference picture in the embodiment of the present application;
Fig. 3 is the schematic diagram of the picture to be detected in the embodiment of the present application;
Fig. 4 is the schematic diagram of the reference picture in the embodiment of the present application after cutting;
Fig. 5 is the schematic diagram of the picture to be detected in the embodiment of the present application after cutting;
Fig. 6 is the schematic diagram of the reference pixel point sequence determined in the embodiment of the present application;
Fig. 7 is the schematic diagram determining the pixel sequence to be detected corresponding to Fig. 6 in the embodiment of the present application;
Fig. 8 is the structural representation of pictorial information treating apparatus in the embodiment of the present application.
Embodiment
In order to make technical problems to be solved in this application, technical scheme and beneficial effect clearly, understand, below in conjunction with drawings and Examples, the application is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the application, and be not used in restriction the application.
Most of picture to be detected is applicable to and the problem of the higher detection method of detection efficiency in order to solve lacking of existing in prior art, a kind of pictorial information disposal route that the embodiment of the present application provides, the method can be applied in pictorial information treating apparatus, its flow process as shown in Figure 1, comprises the steps:
S10: by the first picture to be detected of receiving according to after setting ratio convergent-divergent, the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size.
In picture processing device, store the picture required for oneself, these pictures are just called reference picture, and such as, picture in Fig. 2 can as reference picture.When receive the picture that will upload namely the first picture to be detected time, first judge that whether the first picture to be detected similar to the reference picture that self stores, such as, picture in Fig. 3 can detect picture as first.
Because treat that the size of the first detection picture and reference picture may be different, like this just need setting ratio to carry out convergent-divergent to the first picture to be detected, make the after convergent-divergent second picture to be detected as far as possible consistent with the size of reference picture.By the first picture to be detected according to after setting ratio convergent-divergent, be the sub-pictures of setting size by be detected for second after convergent-divergent and reference picture cutting, the size of sub-pictures can set according to actual needs.
Continue along using example, the schematic diagram after the first picture to be detected and reference picture cutting respectively as shown in Figure 4 and Figure 5.
S11: choose the sub-pictures in the Similar content region of the second picture to be detected and reference picture, as sub-pictures to be detected with reference to sub-pictures.
After by the second picture to be detected and reference picture cutting, certain region can be selected to detect, such as, sub-pictures in the Similar content region of the second picture to be detected and reference picture can be chosen as detected object, sub-pictures in the Similar content region of the choose second picture to be detected and reference picture is as sub-pictures to be detected, in the reference picture chosen with the sub-pictures in the Similar content region of the second picture to be detected as with reference to sub-pictures, two pictures such as shown in Fig. 2 and Fig. 3, only have fractional part different, other parts are all identical, so just can detect in picture and reference picture using second and remove the sub-pictures of the part outside fractional part as detected object, join detection list or detect in sequence.
S12: by the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determines the similarity of each sub-pictures to be detected and corresponding reference sub-pictures.
Because a lot of picture is coloured, and the picture after overcompression process, the impact that noise level of its pixel color value, picture etc. information all can be serious, therefore, needs to do gray proces to picture.In this application, namely to carry out gray proces to the sub-pictures to be detected chosen with reference to sub-pictures, so just can remove its color, obtain such one discolor after gray-scale map, the transition of this gray-scale map is consistent completely with the color transition of the picture carried out before gray proces.Gray scale processing method of the prior art can be adopted, repeat no more here.
By carrying out gray proces to sub-pictures to be detected with reference to sub-pictures, just can obtain the image information only having GTG, so just greatly can get rid of the interference of color, the gray scale variation of brightness after gray proces, can be kept.This way just can avoid pixel inspection technique to be too dependent on the problem of the quality of picture to be detected itself.
S13: according to the similarity determined, determines the similarity of the second picture to be detected and reference picture.
Determine that each sub-pictures to be detected is with after the similarity of corresponding reference sub-pictures, just can determine the similarity of the second picture to be detected and reference picture.
S14: judge whether the similarity of the second picture to be detected and reference picture determined is not less than the first setting threshold value, if so, performs S15; Otherwise, perform S16.
Wherein, this first setting threshold value can be arranged according to actual needs or situation, and when higher to the accuracy requirement of testing result, what the first setting threshold value can be set is larger; When not being very high to the accuracy requirement of testing result, what the first setting threshold value can be set is smaller.
S15: store the first picture to be detected received.
When determining that the similarity of the second picture to be detected and reference picture is not less than the first setting threshold value, just thinking that the first picture to be detected is similar to reference picture, so, just storing the first picture to be detected received.
S16: delete the first picture to be detected received.
When determining that the similarity of the second picture to be detected and reference picture is less than the first setting threshold value, just thinking that the first picture to be detected and reference picture are dissimilar, the first picture to be detected received can be deleted.
The program, by carrying out gray proces to the sub-pictures to be detected chosen with reference to sub-pictures, greatly can be got rid of the interference of color, be no longer dependent on the color of picture to be detected, which increase the accuracy of judgement; By determining to reference to whether sub-pictures is similar, sub-pictures to be detected determines whether that whether picture to be detected is similar to reference picture, thus determine whether to store the picture to be detected received.Because the party is for the size of picture to be detected and the specific requirement of quality, therefore go for most of picture to be detected.
Above-mentioned step is described in further detail below.
Concrete, the process of the determination setting ratio in above-mentioned S10, comprising: in the length direction and Width of reference picture, and the large direction of selected pixels number is as selected directions; And get the pixel count of the first picture to be detected in selected directions and the ratio of the pixel count of reference picture in selected directions, using the ratio obtained as setting ratio.
Because picture convergent-divergent from big to small can not distortion, the distortion and convergent-divergent from small to big is just bound to, thus generally can choose the less picture of size as reference picture according to actual demand when choosing reference picture.Such as: the size of the reference picture chosen is 640*480, the size of picture to be detected is 1024*800, because the pixel count of reference picture length direction is more than the pixel count on Width, can using length direction as selected directions, then the first picture to be detected pixel count in the longitudinal direction and reference picture pixel count are in the longitudinal direction done ratio, namely the ratio 1.6 of 1024 and 640 is got, using 1.6 as setting ratio.The size of the second picture to be detected obtained after the first image zooming to be detected is 640*500 (1024/1.6=640,800/1.6=500).
Concrete, the similarity of each sub-pictures to be detected of the determination in above-mentioned S12 and corresponding reference sub-pictures, comprise: for each sub-pictures to be detected and corresponding reference sub-pictures, perform following operation: choose with the desired location of corresponding reference sub-pictures the pixel setting number at sub-pictures to be detected respectively; Form pixel sequence to be detected by the pixel of the sub-pictures to be detected chosen, and form reference pixel point sequence by the pixel of the reference sub-pictures chosen; Determine the gray scale variation information of pixel sequence to be detected and reference pixel point sequence; And according to the gray scale variation information of the pixel sequence to be detected determined and reference pixel point sequence, determine the similarity of sub-pictures to be detected and corresponding reference sub-pictures.
Each sub-pictures to be detected and the similarity with reference to sub-pictures can be determined successively, the method adopted can have multiple, such as linearity test method, non-linear detection method etc. method, below to adopt linearity test method to be described, because sub-pictures to be detected and reference sub-pictures are rectangles, adopt the region at the inspection place that linearity test method can be maximum, and can picture noise be avoided.
Continue along using example, Fig. 6 and Figure 7 shows that can find out the diagonal line of sub-pictures to be detected and corresponding reference sub-pictures, with this diagonal line for benchmark, detect the linear transitions change of GTG on this line, then the mode quantization means of this change numerical value out.First the pixel of setting number can be chosen on the diagonal line of sub-pictures to be detected, such as on average get 7 pixels, form pixel sequence to be detected, record the gray level information of these 7 pixels, then the gray scale variation information between a rear pixel and previous pixel is calculated, can certainly choose more pixel, the pixel chosen is more, and accuracy is higher; The identical diagonal line of the reference sub-pictures corresponding with sub-pictures to be detected chooses the pixel setting number, composition reference pixel point sequence, record the gray level information of these pixels, then calculate the gray scale variation information between a rear pixel and previous pixel.Sub-pictures to be detected and the similarity with reference to sub-pictures can be determined according to the gray scale variation information of the pixel sequence to be detected obtained and reference pixel point sequence.
Concrete, the gray scale variation information of above-mentioned pixel sequence to be detected according to determining and reference pixel point sequence, determine the similarity of sub-pictures to be detected and corresponding reference sub-pictures, comprise: by the number of gray scale variation information identical in the pixel sequence to be detected determined and the gray scale variation information of reference pixel point sequence, or the ratio of the number of gray scale variation information that the pixel sequence to be detected determined is identical with in the gray scale variation information of reference pixel point sequence and the sum of gray scale variation information, as the similarity of sub-pictures to be detected with corresponding reference sub-pictures.
Continue, along using example, when gray scale variation information is greater than 0, to think that this pixel has brightened relative to previous pixel; When gray scale variation information is less than 0, think that this pixel is dimmed relative to previous pixel.Can with bright, secretly identify gray scale variation information, the number that then pixel sequence more to be detected is identical with the gray scale variation information in reference pixel point sequence, using this number as sub-pictures to be detected and the corresponding similarity with reference to sub-pictures; Or determine the ratio of the number of gray scale variation information that pixel sequence to be detected is identical with in the gray scale variation information of reference pixel point sequence and the sum of gray scale variation information, as the similarity of sub-pictures to be detected with corresponding reference sub-pictures.
Such as: the gray scale variation information in the pixel sequence to be detected determined is " bright, bright, dark, dark, dark, dark, bright ", gray scale variation information in reference pixel point sequence is " bright, dark, dark, dark, dark, bright, bright ", wherein first and third, four, five, seven these 4 gray scale variation information are identical, can using 4 as the similarity of sub-pictures to be detected with corresponding reference sub-pictures; Also can using 4 with the ratio 0.57 of the sum 7 of the gray scale variation information ratio as the sum of gray scale variation information.
Concrete, in above-mentioned S13 according to the similarity determined, determine the similarity of the second picture to be detected and reference picture, specifically comprise: when sub-pictures to be detected is not less than the second setting threshold value with the similarity of corresponding reference sub-pictures, determine that sub-pictures to be detected is similar with corresponding reference sub-pictures; According to the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, determine the similarity of the second picture to be detected and reference picture.
Concrete, the total number of above-mentioned number and sub-pictures to be detected according to determining the to be detected sub-pictures similar with corresponding reference sub-pictures, determine the similarity of the second picture to be detected and reference picture, specifically comprise: the ratio obtaining the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, using the similarity of the ratio of acquisition as the second picture to be detected and reference picture.
Can using the similarity of the ratio of the total number of the number of the to be detected sub-pictures similar with corresponding reference sub-pictures and sub-pictures to be detected as the second picture to be detected and reference picture; Also can using the similarity of the product of the total number of the number of the to be detected sub-pictures similar with corresponding reference sub-pictures and sub-pictures to be detected as the second picture to be detected and reference picture, here the method that two kinds are determined the similarity of the second picture to be detected and reference picture is only listed, method of the prior art can certainly be adopted, repeat no more here.
Based on same inventive concept, a kind of pictorial information treating apparatus that the embodiment of the present application also provides, the structure of this device, as shown in 8 figure, comprising:
Picture cutting unit 80, for receiving first picture to be detected is according to after setting ratio convergent-divergent, and the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size.
Sub-pictures chooses unit 81, for choosing the sub-pictures in the Similar content region of the second picture to be detected and reference picture, as sub-pictures to be detected with reference to sub-pictures.
Sub-pictures similarity determining unit 82, for by the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determines the similarity of each sub-pictures to be detected and corresponding reference sub-pictures.
Picture analogies degree determining unit 83, for according to the similarity determined, determines the similarity of the second picture to be detected and reference picture.
Image store 84, for when the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, stores the first picture to be detected received.
Concrete, above-mentioned picture cutting unit 80, specifically for: the direction that selected pixels number is large in the length direction and Width of reference picture, as selected directions; And get the pixel count of the first picture to be detected in selected directions and the ratio of the pixel count of reference picture in selected directions, using the ratio obtained as setting ratio.
Concrete, above-mentioned sub-pictures similarity determining unit 82, specifically for for each sub-pictures to be detected and corresponding reference sub-pictures, performs: choose with the desired location of corresponding reference sub-pictures the pixel setting number at sub-pictures to be detected respectively; Form pixel sequence to be detected by the pixel of the sub-pictures to be detected chosen, and form reference pixel point sequence by the pixel of the reference sub-pictures chosen; Determine the gray scale variation information of pixel sequence to be detected and reference pixel point sequence; And according to the gray scale variation information of the pixel sequence to be detected determined and reference pixel point sequence, determine the similarity of sub-pictures to be detected and corresponding reference sub-pictures.
Concrete, above-mentioned sub-pictures similarity determining unit 82, specifically for: by the number of gray scale variation information identical in the pixel sequence to be detected determined and the gray scale variation information of reference pixel point sequence, or the ratio of the number of gray scale variation information that the pixel sequence to be detected determined is identical with in the gray scale variation information of reference pixel point sequence and the sum of gray scale variation information, as the similarity of sub-pictures to be detected with corresponding reference sub-pictures.
Concrete, above-mentioned picture analogies degree determining unit 83, specifically for: when sub-pictures to be detected is not less than the second setting threshold value with the similarity of corresponding reference sub-pictures, determine that sub-pictures to be detected is similar with corresponding reference sub-pictures; According to the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, determine the similarity of the second picture to be detected and reference picture.
Concrete, above-mentioned picture analogies degree determining unit 83, specifically for the ratio obtaining the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, using the ratio of the acquisition similarity as the second picture to be detected and reference picture.
Those skilled in the art should understand, the embodiment of the application can be provided as method, system or computer program.Therefore, the application can adopt the form of complete hardware embodiment, completely software implementation or the embodiment in conjunction with software and hardware aspect.And the application can adopt in one or more form wherein including the upper computer program implemented of computer-usable storage medium (including but not limited to magnetic disk memory, CD-ROM, optical memory etc.) of computer usable program code.
The application describes with reference to according to the process flow diagram of the method for the embodiment of the present application, equipment (system) and computer program and/or block scheme.Should understand can by the combination of the flow process in each flow process in computer program instructions realization flow figure and/or block scheme and/or square frame and process flow diagram and/or block scheme and/or square frame.These computer program instructions can being provided to the processor of multi-purpose computer, special purpose computer, Embedded Processor or other programmable data processing device to produce a machine, making the instruction performed by the processor of computing machine or other programmable data processing device produce device for realizing the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
These computer program instructions also can be stored in can in the computer-readable memory that works in a specific way of vectoring computer or other programmable data processing device, the instruction making to be stored in this computer-readable memory produces the manufacture comprising command device, and this command device realizes the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
These computer program instructions also can be loaded in computing machine or other programmable data processing device, make on computing machine or other programmable devices, to perform sequence of operations step to produce computer implemented process, thus the instruction performed on computing machine or other programmable devices is provided for the step realizing the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
Although described the preferred embodiment of the application, those skilled in the art once obtain the basic creative concept of cicada, then can make other change and amendment to these embodiments.So claims are intended to be interpreted as comprising preferred embodiment and falling into all changes and the amendment of the application's scope.
Above-mentioned explanation illustrate and describes the preferred embodiment of the application, but as previously mentioned, be to be understood that the application is not limited to the form disclosed by this paper, should not regard the eliminating to other embodiments as, and can be used for other combinations various, amendment and environment, and can in invention contemplated scope described herein, changed by the technology of above-mentioned instruction or association area or knowledge.And the change that those skilled in the art carry out and change do not depart from the spirit and scope of the application, then all should in the protection domain of the application's claims.
Claims (9)
1. a pictorial information disposal route, is characterized in that, comprising:
By the first picture to be detected of receiving according to after setting ratio convergent-divergent, the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size;
Choose the sub-pictures in the Similar content region of the second picture to be detected and described reference picture, as sub-pictures to be detected with reference to sub-pictures;
By the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determine the similarity of each sub-pictures to be detected and corresponding reference sub-pictures;
According to the similarity determined, determine the similarity of the second picture to be detected and reference picture;
When the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, store the first picture to be detected received;
Wherein, determine the process of described setting ratio, specifically comprise:
The direction that selected pixels number is large in the length direction and Width of reference picture, as selected directions; And
Get the pixel count of the first picture to be detected in described selected directions and the ratio of the pixel count of reference picture in described selected directions, using the ratio obtained as setting ratio.
2. the method for claim 1, is characterized in that, determines each sub-pictures to be detected and the similarity of corresponding reference sub-pictures, specifically comprises:
For each sub-pictures to be detected and corresponding reference sub-pictures, perform:
Choose with the desired location of corresponding reference sub-pictures the pixel setting number respectively at sub-pictures to be detected;
Form pixel sequence to be detected by the pixel of the sub-pictures to be detected chosen, and form reference pixel point sequence by the pixel of the reference sub-pictures chosen;
Determine the gray scale variation information of described pixel sequence to be detected and described reference pixel point sequence; And
According to the gray scale variation information of the pixel sequence described to be detected determined and described reference pixel point sequence, determine the similarity of sub-pictures to be detected and corresponding reference sub-pictures.
3. method as claimed in claim 2, is characterized in that, according to the gray scale variation information of the pixel sequence described to be detected determined and described reference pixel point sequence, determines sub-pictures to be detected and the similarity of corresponding reference sub-pictures, specifically comprises:
By the number of gray scale variation information identical in the pixel sequence described to be detected determined and the gray scale variation information of described reference pixel point sequence, or the ratio of the pixel sequence described to be detected determined and the identical number of gray scale variation information in the gray scale variation information of described reference pixel point sequence and the sum of gray scale variation information, as the similarity of sub-pictures to be detected with corresponding reference sub-pictures.
4. the method for claim 1, is characterized in that, according to the similarity determined, determines the similarity of the second picture to be detected and reference picture, specifically comprises:
When sub-pictures to be detected is not less than the second setting threshold value with the similarity of corresponding reference sub-pictures, determine that described sub-pictures to be detected is similar with corresponding reference sub-pictures;
According to the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, determine the similarity of the second picture to be detected and reference picture.
5. method as claimed in claim 4, is characterized in that, according to the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, determine the similarity of the second picture to be detected and reference picture, specifically comprise:
Obtain the ratio of the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, using the similarity of the ratio of acquisition as the second picture to be detected and reference picture.
6. a pictorial information treating apparatus, is characterized in that, comprising:
Picture cutting unit, for receiving first picture to be detected is according to after setting ratio convergent-divergent, and the second picture cutting to be detected respectively after reference picture and convergent-divergent is the sub-pictures of setting size;
Sub-pictures chooses unit, for choosing the sub-pictures in the Similar content region of the second picture to be detected and described reference picture, as sub-pictures to be detected with reference to sub-pictures;
Sub-pictures similarity determining unit, for by the sub-pictures to be detected chosen with reference to after sub-pictures carries out gray proces, determines the similarity of each sub-pictures to be detected and corresponding reference sub-pictures;
Picture analogies degree determining unit, for according to the similarity determined, determines the similarity of the second picture to be detected and reference picture;
Image store, for when the similarity of the determine second picture to be detected and reference picture is not less than the first setting threshold value, stores the first picture to be detected received;
Wherein, described picture cutting unit, for the direction that selected pixels number in the length direction and Width of reference picture is large, as selected directions; And get the pixel count of the first picture to be detected in described selected directions and the ratio of the pixel count of reference picture in described selected directions, using the ratio obtained as setting ratio.
7. device as claimed in claim 6, it is characterized in that, described sub-pictures similarity determining unit, specifically for for each sub-pictures to be detected and corresponding reference sub-pictures, perform: choose with the desired location of corresponding reference sub-pictures the pixel setting number at sub-pictures to be detected respectively; Form pixel sequence to be detected by the pixel of the sub-pictures to be detected chosen, and form reference pixel point sequence by the pixel of the reference sub-pictures chosen; Determine the gray scale variation information of described pixel sequence to be detected and described reference pixel point sequence; And according to the gray scale variation information of the pixel sequence described to be detected determined and described reference pixel point sequence, determine the similarity of sub-pictures to be detected and corresponding reference sub-pictures.
8. device as claimed in claim 7, it is characterized in that, described sub-pictures similarity determining unit, specifically for the number of gray scale variation information identical in the pixel sequence described to be detected that will determine and the gray scale variation information of described reference pixel point sequence, or the ratio of the pixel sequence described to be detected determined and the identical number of gray scale variation information in the gray scale variation information of described reference pixel point sequence and the sum of gray scale variation information, as the similarity of sub-pictures to be detected with corresponding reference sub-pictures.
9. device as claimed in claim 6, it is characterized in that, described picture analogies degree determining unit, specifically for when sub-pictures to be detected is not less than the second setting threshold value with the similarity of corresponding reference sub-pictures, determines that described sub-pictures to be detected is similar with corresponding reference sub-pictures; According to the number of to be detected sub-pictures similar with corresponding reference sub-pictures determined and the total number of sub-pictures to be detected, determine the similarity of the second picture to be detected and reference picture.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210052031.2A CN103295217B (en) | 2012-03-01 | 2012-03-01 | Pictorial information disposal route and device |
| HK13112079.4A HK1184897A1 (en) | 2012-03-01 | 2013-10-28 | Method for processing image information and device thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210052031.2A CN103295217B (en) | 2012-03-01 | 2012-03-01 | Pictorial information disposal route and device |
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| CN109947965B (en) * | 2017-09-04 | 2023-09-05 | 阿里巴巴集团控股有限公司 | Object recognition, data set updating and data processing method and device |
| CN107832473A (en) * | 2017-11-30 | 2018-03-23 | 奕响（大连）科技有限公司 | A kind of picture similar decision method after non-equal proportion stretching |
| CN107886134A (en) * | 2017-11-30 | 2018-04-06 | 奕响（大连）科技有限公司 | A kind of local creative similar decision method of picture |
| CN108932279A (en) * | 2018-04-28 | 2018-12-04 | 华为技术有限公司 | A kind of application page processing method and processing device |
| CN110490898A (en) * | 2018-05-15 | 2019-11-22 | 苏州欧菲光科技有限公司 | Animation play processing method, liquid crystal instrument system and vehicle based on sequence frame |
| CN112668636B (en) * | 2020-12-25 | 2023-08-08 | 展讯通信（上海）有限公司 | Camera shielding detection method and system, electronic equipment and storage medium |
| CN113139589B (en) * | 2021-04-12 | 2023-02-28 | 网易（杭州）网络有限公司 | Picture similarity detection method and device, processor and electronic device |
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| CN101136015A (en) * | 2006-09-01 | 2008-03-05 | 北大方正集团有限公司 | Method for calculating similarity between images |
| CN101667299A (en) * | 2009-09-27 | 2010-03-10 | 汲业 | Method for staining digital image |
| CN102054177A (en) * | 2010-12-29 | 2011-05-11 | 北京新媒传信科技有限公司 | Image similarity calculation method and device |
| CN102087652A (en) * | 2009-12-08 | 2011-06-08 | 百度在线网络技术（北京）有限公司 | Method for screening images and system thereof |
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| CN101136015A (en) * | 2006-09-01 | 2008-03-05 | 北大方正集团有限公司 | Method for calculating similarity between images |
| CN101667299A (en) * | 2009-09-27 | 2010-03-10 | 汲业 | Method for staining digital image |
| CN102087652A (en) * | 2009-12-08 | 2011-06-08 | 百度在线网络技术（北京）有限公司 | Method for screening images and system thereof |
| CN102054177A (en) * | 2010-12-29 | 2011-05-11 | 北京新媒传信科技有限公司 | Image similarity calculation method and device |
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