CN104599263B

CN104599263B - A kind of method and device of image detection

Info

Publication number: CN104599263B
Application number: CN201410814281.4A
Authority: CN
Inventors: 叶必锭; 吴金勇; 王军
Original assignee: China Security and Surveillance Technology PRC Inc
Current assignee: China Security and Surveillance Technology PRC Inc
Priority date: 2014-12-23
Filing date: 2014-12-23
Publication date: 2017-08-15
Anticipated expiration: 2034-12-23
Also published as: CN104599263A

Abstract

The present invention relates to computer vision intellectual analysis field, more particularly to a kind of method and device of image detection, to solve the problem of current image detecting method is easily caused flase drop.This method includes：Determine the corresponding first intensity of variation value of each pixel in targeted color image, and the second intensity of variation value, according to the first intensity of variation value and the second intensity of variation value, determine the corresponding 3rd intensity of variation value of each pixel in targeted color image, according to the 3rd intensity of variation value, the corresponding prospect degree value of each pixel in targeted color image is determined, according to prospect degree value, the different pixel of background color image in targeted color image is determined.This technical scheme is due to detecting pixel that targeted color image is different from background color image by the 3rd degree changing value, the accuracy for determining the targeted color image pixel different from background color image is improved while the complexity for reducing algorithm, so that reducing causes the possibility of flase drop.

Description

A kind of method and device of image detection

Technical field

The present invention relates to computer vision intellectual analysis field, more particularly to a kind of method and device of image detection.

Background technology

In recent years, with the continuous progress of society, although video monitoring system has been widely used in bank, market, car Stand, the public place such as traffic intersection, but actual monitor task stills need more be accomplished manually.

For example, some domestic businessmans are in order to canvass business orders, often in various buildings, main roads, construct beyond the region of objective existence and stand The vertically hung scroll of various commercial, the height hung due to vertically hung scroll are hung in face, trees, traffic guardrail, river course, enclosure wall and communal facility It is uneven, it is crisscross, not only influence city look and feel, and some vertically hung scrolls are after the suspension long period, the feelings such as appearance is broken, dropped Condition, certain potential safety hazard is constituted to vehicular traffic and pedestrian.

To find the vertically hung scroll of suspension in violation of rules and regulations in time, video monitoring system is introduced.But, traditional video monitoring system by Artificial work shift monitors that because control point is relatively more, staff is less so that much the vertically hung scroll of violations is not sent out in time It is existing.Meanwhile, human eye is easy to cause visual fatigue after long-time stares at monitoring screen, makes decreased attention.With computer Vision technique continuing to develop and applying, it is already possible to replaces human eye and human brain using computer technology, carrys out automatic identification video Image in monitoring system.

In the prior art, image detection is carried out using color histogram, the region of image change is extracted, when existing in scene With monitoring objective color or shape during close object, flase drop is easily caused.

In summary, current image detecting method is easily caused flase drop.

The content of the invention

The embodiments of the invention provide a kind of image detecting method and device, to solve image present in prior art The problem of detection method is easily caused flase drop.

The embodiments of the invention provide a kind of method of image detection, including：

The color value of each pixel in targeted color image and background color image, is determined in targeted color image Each corresponding first intensity of variation value of pixel, and each pixel in targeted color image and background color image Gradient intensity value and gradient direction value, determine the corresponding second intensity of variation value of each pixel, wherein institute in targeted color image Stating the first intensity of variation value is used to represent the picture of corresponding pixel and background color image in same position in targeted color image Intensity of variation of the element in color, the second intensity of variation value is used to represent corresponding pixel and background in targeted color image Pixel intensity of variation on texture of the coloured image in same position；

According to the corresponding first intensity of variation value of each pixel and the second intensity of variation value, determine that target is color The corresponding 3rd intensity of variation value of each pixel in color image, wherein the 3rd intensity of variation value is used to represent in targeted color image The degree that corresponding pixel changes in color and texture simultaneously with background color image in the pixel of same position；

According to the corresponding 3rd intensity of variation value of each pixel, determine that each pixel is corresponding in targeted color image Prospect degree value, wherein the prospect degree value represents in targeted color image corresponding pixel with background color image identical The pixel of position probability simultaneously different in color and texture；

According to the corresponding prospect degree value of each pixel in the targeted color image, determine in the targeted color image The different pixel of the background color image.

Due to determining the 3rd degree changing value according to the first degree changing value and the second degree changing value in the present invention, and lead to Cross the 3rd degree changing value to detect pixel that targeted color image is different from background color image, reduce the complexity of algorithm The accuracy for determining the targeted color image pixel different from background color image is improved while spending, is led so as to reduce Cause the possibility of flase drop.

It is preferred that gradient intensity value and the gradient side of each pixel in targeted color image and background color image To value, the corresponding second intensity of variation value of each pixel in targeted color image is determined, including：

The gradient intensity value and gradient direction value of each pixel in targeted color image and background color image, really The each pixel in coloured image of setting the goal to background color image the pixel of same position the first texture difference value, and really Determine each pixel in background color image to targeted color image the pixel of same position the second texture difference value；

According to the corresponding first texture difference value of each pixel and the second texture difference value, each pixel is determined Corresponding second intensity of variation value.

It is preferred that the gradient intensity value and ladder of each pixel in the targeted color image and the background color image Degree direction value meets following equation：

Wherein, x represents the abscissa of the pixel in targeted color image and background color image；Y represents targeted color figure The ordinate of pixel in picture and background color image；(x, y) is represented in targeted color image and background color image where pixel Position；DT^fb(x, y) represents the pixel of (x, y) position in targeted color image to (x, the y) position in background color image Pixel the first texture difference value；DT^bf(x, y) represents the pixel of (x, y) position in background color image to color in target Second texture difference value of the pixel of (x, y) position in color image；S is the image block centered on location of pixels (x, y)；u,v For in S with coordinate that (x, y) is origin；For in targeted color image (x, y) position pixel gradient intensity value； For in target image (x, y) position pixel gradient direction value；Represent in background color image in (x, y) position The gradient intensity value of pixel；Represent background color image in (x, y) position pixel gradient direction value.

It is preferred that each 3rd intensity of variation value meets following equation：

Wherein, P (x, y) represents the corresponding prospect degree of pixel in (x, y) position in targeted color image；D (x, y) table Show the 3rd intensity of variation value；α represents gain；β represents biasing.

It is preferred that determining background color image according to following manner：

For the multiple image of the continuous acquisition from video capture device, it is determined that the mixing of each pixel in per two field picture Gauss model；

The priority of Gaussian Profile in the mixed Gauss model of each pixel in every two field picture, it is determined that described The background distributions of each pixel in per two field picture；

The background distributions of each pixel in every two field picture of determination, determine the background image.

It is preferred that according to the corresponding prospect degree value of each pixel in the targeted color image, determining that the target is color The different pixel of background color image described in color image, including：

According to the corresponding prospect degree value of each pixel in the targeted color image, the targeted color image is changed Into binary map；

Determine the different pixel of background color image described in the targeted color image；

If it is determined that the number of pixel different from the background color image in the targeted color image is pre- less than first If threshold value, a targeted color image is redefined, returns and determines the first intensity of variation value and the second intensity of variation value The step of, and the background color image according to the targeted color image update.

Due to targeted color image is converted into binary map according to prospect degree value, the complexity of algorithm is significantly reduced Degree, due to by it is determined that the number of pixel not different from background color image in targeted color image is preset less than first After threshold value, redefine a targeted color image and detected again, the accuracy of image detection is improved, due to it is determined that mesh The number of the not no pixel different from the background color image of coloured image is marked less than after the first predetermined threshold value, according to target Coloured image updates background color image, so as to further increase the accuracy to targeted color image detection.

It is preferred that after determining pixels different from the background color image in the targeted color image, in addition to：

If it is determined that the number of pixel different from the background color image in the targeted color image is not less than first Predetermined threshold value, is extracted in the binary map being converted into by the targeted color image by particular pixel group according to the number of specific pixel Into at least one connected region, wherein, specific pixel represents that the targeted color image and the background image are asynchronous Pixel in the corresponding binary map being converted into by the targeted color image of pixel；

For a connected region, the width and height of the connected region minimum enclosed rectangle are determined, according to the width Degree and the height, after it is determined that the connected region meets selection condition, determine the gray level image of the connected region, and will The greyscale image transitions of determination are into binary map；

According to the greyscale image transitions by each connected region into binary map, determine whether marker connected region.

Because the binary map being converted into according to the connected region for being determined for compliance with selection condition determines whether there is the company of mark Logical region, that is to say, that in targeted color image whether marker, further reduced while image detection accuracy rate is improved Cause the possibility of flase drop in test pattern.

It is preferred that judging whether the connected region meets selection condition according to following manner：

If the width and the ratio of the height are more than the second predetermined threshold value, it is determined that the connected region meets selection Condition；

If the ratio of the height and the width is more than the 3rd predetermined threshold value, it is determined that the connected region meets selection Condition；

If the width and the ratio of the height are not more than the second predetermined threshold value, and the ratio of the height and the width Value is not more than the 3rd predetermined threshold value, it is determined that the connected region does not meet selection condition.

It is preferred that according to the greyscale image transitions by each connected region into binary map, determine whether marker connect Logical region, including：

For a connected region, if the width of the connected region minimum enclosed rectangle and the ratio of height are more than described Second predetermined threshold value, then according to the greyscale image transitions by the connected region into the gray value of each pixel of binary map exist Vertical direction project obtaining drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that described Connected region is marker connected region, will be by the connected region if the crest quantity of drop shadow curve is not more than the 4th threshold value The greyscale image transitions in domain into the gray value of each pixel of binary map inverted, according to the gray value after reversion vertical Direction project obtaining drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the connection Region is marker connected region；

For a connected region, the height of the connected region minimum enclosed rectangle and the ratio of width are more than described the Three predetermined threshold values, then according to by the connected region greyscale image transitions into binary map each pixel gray value in water Square projected to progress and to obtain drop shadow curve, if the crest quantity of statistics drop shadow curve is more than the 4th predetermined threshold value, it is determined that institute It is marker connected region to state connected region, if the crest quantity of drop shadow curve is not more than the 4th threshold value, will be by the connection The greyscale image transitions in region into the gray value of each pixel of binary map inverted, according to the gray value after reversion in water Square projected to progress and to obtain drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the company Logical region is marker connected region.

The embodiments of the invention provide a kind of device of image detection, including：

First degree value determining module, the face for each pixel in targeted color image and background color image Colour, determines the corresponding first intensity of variation value of each pixel in targeted color image, and according to targeted color image and the back of the body The gradient intensity value and gradient direction value of each pixel in scape coloured image, determine each pixel correspondence in targeted color image The second intensity of variation value, wherein the first intensity of variation value be used for represent corresponding pixel and background in targeted color image Coloured image is in intensity of variation of the pixel in color of same position, and the second intensity of variation value is used to represent targeted color Intensity of variation of the pixel on texture of corresponding pixel and background color image in same position in image；

Second degree value determining module, for according to the corresponding first intensity of variation value of each pixel and described Two intensity of variation values, determine the corresponding 3rd intensity of variation value of each pixel in targeted color image, wherein the 3rd intensity of variation Be worth for represent corresponding pixel and background color image in targeted color image same position pixel simultaneously in color and The degree changed on texture；

Prospect degree value determining module, for according to the corresponding 3rd intensity of variation value of each pixel, determining target The corresponding prospect degree value of each pixel in coloured image, wherein the prospect degree value represents corresponding in targeted color image Pixel is from background color image in the pixel of same position probability simultaneously different in color and texture；

Pixel determining module, for according to the corresponding prospect degree value of each pixel in the targeted color image, it is determined that The pixel different from the background color image in the targeted color image.

It is preferred that the first degree value determining module specifically for：

It is preferred that described device also includes：

Background color image determining module, for determining background color image according to following manner：

The background distributions of each pixel in every two field picture of determination, determine the background color image.

It is preferred that the prospect degree value determining module specifically for：

According to the corresponding prospect degree value of each pixel in the targeted color image, the targeted color image is changed Into binary map；Determine the different pixel of background color image described in the targeted color image；

The device also includes：

Return to module, the number for determining pixels different from the background color image in the targeted color image Less than the first predetermined threshold value, a targeted color image is redefined, returns and determines the first intensity of variation value and described second The step of intensity of variation value, and the background color image according to the targeted color image update.

It is preferred that the device also includes：

Judge module, the number for determining pixels different from the background color image in the targeted color image After the first predetermined threshold value, extracted according to the number of specific pixel in the binary map being converted into by the targeted color image At least one connected region being made up of specific pixel, wherein, specific pixel represents the targeted color image and the background Pixel in the corresponding binary map being converted into by the targeted color image of the asynchronous pixel of coloured image；For a company Logical region, determines the width and height of the connected region minimum enclosed rectangle, according to the width and the height, it is determined that The connected region meets after selection condition, determines the gray level image of the connected region, and by the greyscale image transitions of determination Into binary map；According to the greyscale image transitions by each connected region into binary map, determine whether marker connected region.

Brief description of the drawings

Fig. 1 is the flow chart of the method for the image detection of the embodiment of the present invention one；

Fig. 2 is the minimum enclosed rectangle schematic diagram of the connected region of the embodiment of the present invention two；

Fig. 3 is the flow chart of the method for the image detection of the embodiment of the present invention three；

Fig. 4 is the flow chart that the embodiment of the present invention four determines to have the method for marker in image；

Fig. 5 is the flow chart of the method for the image detection of the embodiment of the present invention five；

Fig. 6 is the schematic diagram of the device of the image detection of the embodiment of the present invention six.

Embodiment

The color value of each pixel of the embodiment of the present invention in targeted color image and background color image, determines mesh The corresponding first intensity of variation value of each pixel in coloured image is marked, and according in targeted color image and background color image Each pixel gradient intensity value and gradient direction value, determine the corresponding second change journey of each pixel in targeted color image Angle value, wherein the first intensity of variation value is used to represent that corresponding pixel and background color image to be in identical bits in targeted color image Intensity of variation of the pixel put in color, the second intensity of variation value is used to represent corresponding pixel and the back of the body in targeted color image Pixel intensity of variation on texture of the scape coloured image in same position；According to the corresponding first intensity of variation value of each pixel And the second intensity of variation value, the corresponding 3rd intensity of variation value of each pixel in targeted color image is determined, wherein the 3rd becomes Changing degree value is used to represent in targeted color image that pixel of the corresponding pixel with background color image in same position to exist simultaneously The degree changed in color and texture；According to the corresponding 3rd intensity of variation value of each pixel, determine every in targeted color image The corresponding prospect degree value of individual pixel, wherein prospect degree value represent corresponding pixel and background color figure in targeted color image As same position pixel simultaneously in color and texture different probability；It is corresponding according to each pixel in targeted color image Prospect degree value, determines the different pixel of background color image in targeted color image.This technical scheme is due in the present invention 3rd degree changing value is determined according to the first degree changing value and the second degree changing value, and examined by the 3rd degree changing value The targeted color image pixel different from background color image is surveyed, determination mesh is improved while the complexity for reducing algorithm The accuracy of the coloured image pixel different from background color image is marked, so that reducing causes the possibility of flase drop.

The embodiment of the present invention is described in further detail with reference to Figure of description.

As shown in figure 1, the method for the image detection of the embodiment of the present invention one, including：

Step 100, the color value of each pixel in targeted color image and background color image, determines that target is color The corresponding first intensity of variation value of each pixel in color image, and it is every in targeted color image and background color image The gradient intensity value and gradient direction value of one pixel, determine corresponding second intensity of variation of each pixel in targeted color image Value, wherein the first intensity of variation value is used to represent that corresponding pixel and background color image to be in same position in targeted color image Intensity of variation of the pixel in color, the second intensity of variation value is used to represent corresponding pixel and background in targeted color image Pixel intensity of variation on texture of the coloured image in same position；

Step 101, according to the corresponding first intensity of variation value of each pixel and the second intensity of variation value, determine that target is color The corresponding 3rd intensity of variation value of each pixel in color image, wherein the 3rd intensity of variation value is used to represent in targeted color image The degree that corresponding pixel changes in color and texture simultaneously with background color image in the pixel of same position；

Step 102, according to the corresponding 3rd intensity of variation value of each pixel, each pixel pair in targeted color image is determined The prospect degree value answered, wherein prospect degree value represent in targeted color image corresponding pixel with background color image identical The pixel of position probability simultaneously different in color and texture；

Step 103, according to the corresponding prospect degree value of each pixel in targeted color image, determine in targeted color image The different pixel of background color image.

It should be noted that it is that targeted color image can be obtained by photo or by a certain moment from regarding Obtained in frequency collecting device, the mode of targeted color image can be obtained by being also not necessarily limited to other.

Background color image preferably acquisition modes are：

For example, the two field picture of video capture device continuous acquisition 500, often gathers a two field picture and determines respectively in the two field picture often The mixed Gauss model of individual pixel, due to there is K Gaussian Profile in mixed Gauss model, it is assumed that K=3, is then determined each respectively Corresponding 3 Gaussian Profiles of pixel, wherein corresponding 3 Gaussian Profiles of each pixel are carried out from big to small according to the value of priority Arrangement, takes the preceding B branch of corresponding 3 Gaussian Profiles of each pixel, it is assumed that B=2, as background distributions, to each picture The weights of the corresponding background distributions of element and mean value weighting summation obtain color value, by the corresponding face of each pixel in 500 two field pictures Colour constitutes the background color image at current time.

Specifically, the value of priority is determined according to one of following equation：

Or λ_i=ω_i (2)

Wherein, λ_iRepresent the value of the priority of i-th of Gaussian Profile；ω_iRepresent the weight of i-th of Gaussian Profile；σ_iRepresent The variance of i-th of Gaussian Profile.

It is determined that each pixel i-th of Gaussian Profile priority value when, if using formula (1), not using Formula (2)；Vice versa.That is it is determined that each pixel i-th of Gaussian Profile priority value when, do not hand over preferably Fork uses formula (1) and formula (2).

And the corresponding color value of pixel in background color image in (x, y) position meets formula (3)：

Wherein, bg (x, y) represents the corresponding color value of pixel in (x, y) position in background color image；ω_iRepresent the The weight of i Gaussian Profile；σ_iThe variance of i-th of Gaussian Profile is represented, B represents background distributions.

Wherein, the first intensity of variation value is obtained by color difference formula (4)：

DC (x, y)=max (abs (r (x, y)-bg_r(x,y),abs(g(x,y)-bg_g(x,y)),abs(b(x,y)-bg_b (x,y))) (4)

In color difference formula (4), DC (x, y) represents the first intensity of variation value；X represents targeted color image and background The abscissa of pixel in coloured image；Y represents the ordinate of pixel in targeted color image and background color image；(x,y) Represent the position where pixel in targeted color image and background color image；R (x, y), g (x, y), b (x, y) represent mesh respectively Mark coloured image in position (x, y) pixel red, green, blue triple channel color value；bg_r(x,y)、bg_g(x,y)、bg_b(x, Y) respectively represent background color image in position (x, y) pixel red, green, blue triple channel color value.

In targeted color image corresponding pixel and background color image same position simultaneously in color and texture not Same probability, that is to say, that corresponding pixel is not belonging to the probability that background color image belongs to prospect in targeted color pixel, is needed It is noted that the composition prospect different from pixel in background color image.

It is preferred that the gradient intensity value and ladder of each pixel in the targeted color image and the background color image Degree direction value meets formula (5)：

The gradient intensity value and gradient direction of each pixel in the targeted color image and the background color image Value meets formula (6)：

Specifically, image block S may be sized in 13*13, targeted color image and background color image The gradient (including gradient intensity value and gradient direction value) of the pixel of position (x, y) can use what is commonly used in Digital Image Processing Coloured image gradient calculation method is obtained.

It is preferred that according to the corresponding first texture difference value of each pixel and the second texture difference value, it is determined that The corresponding second intensity of variation value of each pixel, including：

Using value larger in the corresponding first texture difference value of each pixel and the second texture difference value as The corresponding second intensity of variation value of each pixel.

That is, the second intensity of variation value DT (x, y)=max (DT^fb(x,y),DT^bf(x,y))。

It is preferred that each 3rd intensity of variation value meets formula (7)：

Wherein, P (x, y) represents the corresponding prospect degree value of pixel in (x, y) position in targeted color image；D(x,y) Represent the 3rd intensity of variation value；α represents gain；β represents biasing.

Wherein, gain alpha, biasing β are, according to the different according to being configured the need for user of actual conditions, to be mainly used in D (x, y) size is adjusted, so that obtained P (x, y) is more accurate.

It is preferred that in step 103, specifically, according to the corresponding prospect degree value of each pixel in targeted color image, Targeted color image is converted into binary map；

Determine the different pixel of background color image described in the targeted color image.

That is, according to the corresponding prospect degree value of each pixel in targeted color image, will by thresholding method Targeted color image is converted into binary map, and its specific practice is as follows：

So that the pixel in binary map includes white pixel and black picture element as an example, related description is carried out, binaryzation is will be greater than Pixel in the corresponding targeted color image of prospect degree value of threshold value is expressed as white pixel, by no more than binary-state threshold Pixel in the corresponding targeted color image of prospect degree value is expressed as black picture element, and the threshold value of wherein binaryzation is according to reality Respective settings are carried out in situation the need for user, for example binary-state threshold could be arranged to 0.5.

Pixel in the corresponding targeted color image of its white pixel is exactly the pixels different from background color image.

It should be noted that the pixel in binary map is two different colors of pixel, white pixel is not restricted to And black picture element, it can also represent that the pixel in corresponding targeted color image is exactly and background color with the pixel of other colors The different pixel of image, as long as with representing the pixel in targeted color image in the binary map that is converted into by targeted color image just Be color corresponding from background color image identical pixel pixel it is different.

It is preferred that after determining the different pixels of background color image described in the targeted color image, however, it is determined that institute The number for stating pixels different from the background color image in targeted color image is less than the first predetermined threshold value, redefines one Targeted color image, and return to the step of determining the first intensity of variation value and the second intensity of variation value.

First predetermined threshold value is according to being set the need for user in actual conditions, if being changed by targeted color image Into binary map in only isolated several expressions pixel different from respective pixel in background color image, also by targeted color Spectral discrimination be and the pixel identical situation in background color image.

That is, can be after it is determined that the color of object image of collection be identical with background color image, when default Between redefine targeted color image, can also it is determined that collection color of object image it is identical with background color image after, Directly redefine targeted color image.

It is preferred that determining that the number of pixels different from the background color image in the targeted color image is less than the After one predetermined threshold value, the background color image according to targeted color image update.

Its detailed process is：Mixed Gauss model is updated using each pixel of targeted color image, updated Afterwards, choose the Gaussian Profile that priority is preceding B and be defined as background distributions, it is corresponding to each pixel in new background distributions The average of background distributions obtains color value as weighted sum, and obtained all colours value is constituted into the background color figure after updating Picture.

It should be noted that mixed Gaussian will be set up to each pixel in the image that is gathered from video capture device Model, and determine the priority that K is distributed in mixed Gauss model according to a formula in formula (1) and formula (2).Every Background color image is updated every preset time, or after it is determined that the coloured image of target is identical with background color image, Background color image is updated.

It is preferred that after determining pixels different from background color image in targeted color image, however, it is determined that targeted color The number of the pixel different from background color image is not less than the first predetermined threshold value in image, is extracted according to the number of specific pixel At least one connected region being made up of in the binary map being converted into by targeted color image specific pixel, wherein, specific pixel Represent in the targeted color image binary map being converted into by targeted color image corresponding with the asynchronous pixel of background image Pixel；

For a connected region, the width and height of connected region minimum enclosed rectangle are determined, according to width and height, After it is determined that connected region meets selection condition, determine the gray level image of connected region, and by the greyscale image transitions of determination into Binary map；

Wherein, marker can be vertically hung scroll, Sign Board or other marks different from background.

If it is determined that there is marker connected region, then illustrate there is marker in targeted color image, then send alarm, otherwise weigh It is new to determine a targeted color image, return to the step of determining the first intensity of variation value and the second intensity of variation value.

It can then illustrate there is mark in targeted color image after it is determined that connected region is marker connected region Thing, then no longer carry out continuation judgement, send alarm；Can also be it is determined that whether all connected regions be marker connected region Afterwards, if so, then sending alarm, a targeted color image is otherwise redefined, returns and determines the first intensity of variation value and institute The step of stating the second intensity of variation value.

So that the binary map that is converted into by targeted color image is constituted by white pixel and with black picture element as an example, wherein by mesh Pixels different from background color image are expressed as white pixel in mark coloured image, using the opening operation in morphology and close Computing is handled the binary map being converted into by targeted color image, removes some in the connected region being made up of white pixel Isolated black picture element, and upper white pixel is filled into the position where former black picture element, according to white pixel in connected region Number, extract connected region.The number of white pixel extracts connected region for how many when in specific connected region, is according to reality Set in the situation of border the need for user.

The width and height of connected region are determined according to the minimum enclosed rectangle of its connected region, as shown in Fig. 2 connected region The minimum enclosed rectangle in domain 200 is 201.

Wherein the second predetermined threshold value and the 3rd predetermined threshold value be according to user in actual conditions the need for carry out related setting , the second predetermined threshold value and the 3rd predetermined threshold value can be identical value, or different values, such as the second predetermined threshold value Can take 5 simultaneously with the 3rd predetermined threshold value, can also the second predetermined threshold value go 6, the 3rd predetermined threshold value takes 5.

If without qualified connected region, then redefining a targeted color image, return and determine described first The step of intensity of variation value and the second intensity of variation value.

It is preferred that according to the greyscale image transitions by each connected region into binary map, determine whether marker connect Logical region：

For a connected region, if the width of the connected region minimum enclosed rectangle and the ratio of height are more than described Second predetermined threshold value, then according to the greyscale image transitions by the connected region into the gray value of each pixel of binary map exist Vertical direction project obtaining drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that described Connected region is marker connected region；, will be by the connected region if the crest quantity of drop shadow curve is not more than the 4th threshold value The greyscale image transitions in domain into the gray value of each pixel of binary map inverted, according to the gray value after reversion vertical Direction project obtaining drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the connection Region is marker connected region；

For a connected region, the height of the connected region minimum enclosed rectangle and the ratio of width are more than described the Three predetermined threshold values, then according to by the connected region greyscale image transitions into binary map each pixel gray value in water Square projected to progress and to obtain drop shadow curve, if the crest quantity of statistics drop shadow curve is more than the 4th predetermined threshold value, it is determined that institute It is marker connected region to state connected region, if the crest quantity of drop shadow curve is not more than the 4th threshold value, will be by the connection The greyscale image transitions in region into the gray value of each pixel of binary map inverted, according to the gray value after reversion in water Square projected to progress and to obtain drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the company Logical region is marker connected region；

4th predetermined threshold value is set according to the need for user in actual conditions.

It should be noted that the gray level image of qualified connected region can be converted into binary map by following manner：

The targeted color image obtained from video capture device is converted into gray level image by formula (8)：

Gray (x, y)=0.299*r (x, y)+0.587*g (x, y)+0.144*b (x, y) (8)

Wherein, gray (x, y) represents gray value of the targeted color image in the pixel of position (x, y)；X represents targeted color The abscissa of pixel in image；Y represents the ordinate of pixel in targeted color image；(x, y) is represented in targeted color image Position where pixel；R (x, y), g (x, y), b (x, y) respectively represent the pixel at position (x, y) in targeted color image The color value of red, green, blue triple channel.

Further according to the coordinate position of qualified connected region, cut in the gray level image being converted into from targeted color image Take the gray level image of relevant position.

Connected region corresponding gray level image will be obtained two-value is translated into by the OTSU methods in Digital Image Processing Figure, wherein binary map are made up of any two different colors of pixel, are illustrated by taking white pixel and black picture element as an example, black The gray value of color pixel is 0, and the gray value of white pixel is 255.Black picture element in the binary map being converted into by connected region The pixel in correspondence background color image may be represented, it is also possible to represent the pixel in corresponding targeted color image, work as black When pixel represents the pixel in correspondence background color image, white pixel represents the pixel in correspondence targeted color image；When black When color pixel represents the pixel in correspondence targeted color image, white pixel represents the pixel in correspondence background color image.

For example when marker is the vertically hung scroll for having character, the binary map changed into by connected region is character and background color The combination of the brightness of image, wherein, when character is white pixel, background color image is black picture element；Otherwise background color figure As being white pixel, character is black picture element.

Therefore after drop shadow curve is obtained, if crest quantity when being not more than four predetermined threshold values, it is necessary to which gray value is entered Row reversion, is judged again, that is to say, that if the gray value of black picture element is 0, and the gray value of white pixel is 255, then instead The gray value of black picture element is 255 after turning, and the gray value of white pixel is 0.

If the width of the connected region minimum enclosed rectangle and the ratio of height are more than second predetermined threshold value, also To say that marker is horizontally suspended, then according to by the connected region greyscale image transitions into binary map each pixel ash Angle value is projected in vertical direction；If the height of the connected region minimum enclosed rectangle and the ratio of width are more than described the Three predetermined threshold values, that is to say, that marker vertical hanging, then according to by the connected region greyscale image transitions into two-value The gray value of each pixel of figure is projected in the horizontal direction.

If after projecting twice, the quantity of drop shadow curve is all not more than the 4th predetermined threshold value, then does not have in targeted color image There is marker.

As shown in figure 3, the image detecting method of the embodiment of the present invention three, including：

Step 300, the binary map changed into by targeted color image is entered using the opening operation in morphology and closed operation Row processing.

Step 301, extract and targeted color image and background image are represented in the binary map being converted into by targeted color image At least one connected region that pixel in the corresponding binary map being converted into by targeted color image of asynchronous pixel is constituted；

Step 302, for a connected region, the width and height of connected region minimum enclosed rectangle are determined, according to width Degree and height, after it is determined that connected region meets selection condition, determine the gray level image of connected region, and by the gray-scale map of determination As being converted into binary map；

Step 303, according to the greyscale image transitions by each connected region into binary map, determine whether marker connect Logical region.

As shown in figure 4, the embodiment of the present invention four determines the method for having marker in image, including：

Step 400, targeted color image is converted into gray-scale map.

Step 401, the gray-scale map of qualified connected region is intercepted.

Step 402, the gray-scale map of qualified connected region is converted into binary map.

Step 403, the binary map that connected region is changed into is made to the projection of horizontal or vertical direction.

Step 404, judge whether the number of drop shadow curve's medium wave peak is more than the 4th predetermined threshold value, if crest number is more than the Four predetermined threshold values, then perform step 405, otherwise performs step 406.

Step 405, determine there is marker in targeted color image, this flow terminates.

Step 406, obtain new by even after the gray value reversion of each pixel in binary map connected region changed into Logical regioinvertions into binary map, make the projection of horizontal or vertical direction.

Step 407, judge whether the number of drop shadow curve's medium wave peak is more than the 4th predetermined threshold value, if crest number is more than the Four predetermined threshold values, then perform step 405, otherwise performs step 408.

Step 408, determine there is no marker in targeted color image, this flow terminates.

As shown in figure 5, the method for the image detection of the embodiment of the present invention five, including：

Step 500, according to many color image frames obtained from video capture device, determine to carry on the back by mixed Gauss model Scape coloured image.

Step 501, a new frame targeted color image is obtained from video equipment.

Step 502, according to the color value of each pixel in targeted color image and background color image, color difference is passed through Formula determines that the first intensity of variation value, and the gradient intensity value and gradient direction value of each pixel determine the second intensity of variation Value.

Step 503, it regard value larger in the first intensity of variation value and the second intensity of variation value as the 3rd intensity of variation value.

Step 504, the corresponding prospect journey of each pixel in targeted color image is determined according to the 3rd intensity of variation value Angle value.

Step 505, according to the corresponding prospect degree value of each pixel in targeted color image, targeted color image is converted As binary map.

Step 506, binary map is transformed into according to by targeted color image, judges whether have and carry on the back in targeted color image The different pixel of scape coloured image, performs step 508 if having, and otherwise performs step 507.

Step 507, according to targeted color image update background color image, after background color image is updated, step is performed Rapid 501.

Step 508, extract in the binary map being converted into by the targeted color image by expression targeted color image and the back of the body Pixel in the corresponding binary map being converted into by targeted color image of the asynchronous pixel of scape coloured image constitute at least one Individual connected region.

Step 509, judge whether the minimum enclosed rectangle of connected region meets preparatory condition, if meeting, perform step 510, otherwise perform step 507.

Step 510, according to the greyscale image transitions by each connected region into binary map, judge qualified connection Whether region is marker connected region, if so, then performing step 511, otherwise performs step 507.

Step 511, it is determined that having marker in the targeted color image of detection, alarm is sent, this flow terminates.

Based on same inventive concept, a kind of device of image detection is additionally provided in the embodiment of the present invention, due to the present invention The corresponding method of device of embodiment image detection is the method for image detection, therefore the implementation of device of the embodiment of the present invention can be with Referring to the implementation of method, repeat part and repeat no more.

As shown in fig. 6, the device of the image detection of the embodiment of the present invention six, including：

First degree value determining module 600, for each pixel in targeted color image and background color image Color value, determine the corresponding first intensity of variation value of each pixel in targeted color image, and according to targeted color image With the gradient intensity value and gradient direction value of each pixel in background color image, each pixel in targeted color image is determined Corresponding second intensity of variation value, wherein the first intensity of variation value be used to representing in targeted color image corresponding pixel with Background color image is in intensity of variation of the pixel in color of same position, and the second intensity of variation value is used to represent target Intensity of variation of the pixel on texture of corresponding pixel and background color image in same position in coloured image；

Second degree value determining module 601, for according to the corresponding first intensity of variation value of each pixel and institute The second intensity of variation value is stated, the corresponding 3rd intensity of variation value of each pixel in targeted color image is determined, wherein the 3rd change Degree value is used to represent the pixel of corresponding pixel and background color image in targeted color image in same position simultaneously in face The degree changed on color and texture；

Prospect degree value determining module 602, for according to the corresponding 3rd intensity of variation value of each pixel, determining mesh The corresponding prospect degree value of each pixel in coloured image is marked, wherein the prospect degree value represents correspondence in targeted color image Pixel and background color image in the pixel of same position probability simultaneously different in color and texture；

Pixel determining module 603, for according to the corresponding prospect degree value of each pixel in the targeted color image, really The pixel different from the background color image in the fixed targeted color image.

It is preferred that the first degree value determining module 600 specifically for：

It is preferred that the gradient intensity value and ladder of each pixel in the targeted color image and the background color image Degree direction value meets formula：

It is preferred that the second degree value determining module 601 specifically for：

It is preferred that described device also includes：

Background color image determining module 604, for determining background color image according to following manner：

It is preferred that the pixel determining module 603 specifically for：

It is preferred that the device also includes：

Module 605 is returned to, for determining in the targeted color image the not picture different from the background color image The number of element is less than the first predetermined threshold value, redefines a targeted color image, and return to determination the first intensity of variation value The step of with the second intensity of variation value.

It is preferred that the return module 605 is additionally operable to：

Determine that the number of the pixel different from the background color image is not less than first in the targeted color image After predetermined threshold value, the background color image according to the targeted color image update.

It is preferred that the device also includes：

Judge module 606, for determining pixels different from the background color image in the targeted color image Number is not less than after the first predetermined threshold value, and the two-value being converted into by the targeted color image is extracted according to the number of specific pixel At least one connected region being made up of in figure specific pixel, wherein, specific pixel represent the targeted color image with it is described Pixel in the corresponding binary map being converted into by the targeted color image of the asynchronous pixel of background color image；For one Individual connected region, determines the width and height of the connected region minimum enclosed rectangle, according to the width and the height, Determine that the connected region meets after selection condition, determine the gray level image of the connected region, and by the gray level image of determination It is converted into binary map；According to the greyscale image transitions by each connected region into binary map, determine whether marker connect Region.

It is preferred that judge module 606 judges whether the connected region meets selection condition according to following manner：

It is preferred that judge module 606 according to the greyscale image transitions by each connected region into binary map, judge whether There is marker connected region：

The color value of each pixel of the embodiment of the present invention in targeted color image and background color image, determines mesh The corresponding first intensity of variation value of each pixel in coloured image is marked, and according in targeted color image and background color image Each pixel gradient intensity value and gradient direction value, determine the corresponding second change journey of each pixel in targeted color image Angle value, wherein the first intensity of variation value is used to represent that corresponding pixel and background color image to be in identical bits in targeted color image Intensity of variation of the pixel put in color, the second intensity of variation value is used to represent corresponding pixel and the back of the body in targeted color image Pixel intensity of variation on texture of the scape coloured image in same position；According to the corresponding first intensity of variation value of each pixel And the second intensity of variation value, the corresponding 3rd intensity of variation value of each pixel in targeted color image is determined, wherein the 3rd becomes Changing degree value is used to represent in targeted color image that pixel of the corresponding pixel with background color image in same position to exist simultaneously The degree changed in color and texture；According to the corresponding 3rd intensity of variation value of each pixel, determine every in targeted color image The corresponding prospect degree value of individual pixel, wherein prospect degree value represent corresponding pixel and background color figure in targeted color image As same position pixel simultaneously in color and texture different probability；It is corresponding according to each pixel in targeted color image Prospect degree value, determines the different pixel of background color image in targeted color image.This technical scheme is due in the present invention 3rd degree changing value is determined according to the first degree changing value and the second degree changing value, and examined by the 3rd degree changing value The targeted color image pixel different from background color image is surveyed, determination mesh is improved while the complexity for reducing algorithm The accuracy of the coloured image pixel different from background color image is marked, so that reducing causes the possibility of flase drop, is solved The problem of in the prior art image detection is easily caused flase drop.

It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program Product.Therefore, the present invention can be using the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware Apply the form of example.Moreover, the present invention can be used in one or more computers for wherein including computer usable program code The computer program production that usable storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.) The form of product.

The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product Figure and/or block diagram are described.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided The processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.

These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which is produced, to be included referring to Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or The function of being specified in multiple square frames.

These computer program instructions can be also loaded into computer or other programmable data processing devices so that in meter Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one The step of function of being specified in individual square frame or multiple square frames.

, but those skilled in the art once know basic creation although preferred embodiments of the present invention have been described Property concept, then can make other change and modification to these embodiments.So, appended claims are intended to be construed to include excellent Select embodiment and fall into having altered and changing for the scope of the invention.

Obviously, those skilled in the art can carry out the essence of various changes and modification without departing from the present invention to the present invention God and scope.So, if these modifications and variations of the present invention belong to the scope of the claims in the present invention and its equivalent technologies Within, then the present invention is also intended to comprising including these changes and modification.

Claims

1. a kind of method of image detection, it is characterised in that this method includes：

The color value of each pixel in targeted color image and background color image, is determined each in targeted color image The corresponding first intensity of variation value of pixel, and each pixel in targeted color image and background color image gradient Intensity level and gradient direction value, determine the corresponding second intensity of variation value of each pixel in targeted color image, wherein described One intensity of variation value is used to represent that corresponding pixel to exist with background color image in the pixel of same position in targeted color image Intensity of variation in color, the second intensity of variation value is used to represent corresponding pixel and background color in targeted color image Pixel intensity of variation on texture of the image in same position；

According to the corresponding first intensity of variation value of each pixel and the second intensity of variation value, targeted color figure is determined The corresponding 3rd intensity of variation value of each pixel as in, wherein the 3rd intensity of variation value is used to represent correspondence in targeted color image The degree that changes simultaneously in color and texture in the pixel of same position of pixel and background color image；

According to the corresponding 3rd intensity of variation value of each pixel, the corresponding prospect of each pixel in targeted color image is determined Degree value, wherein the prospect degree value represents that corresponding pixel and background color image are in same position in targeted color image Pixel probability different in color and texture simultaneously；

Wherein, each 3rd intensity of variation value meets following equation：

P (x, y) represents the corresponding prospect degree of pixel in (x, y) position in targeted color image；D (x, y) represents described the Three intensity of variation values；α represents gain；β represents biasing；

According to the corresponding prospect degree value of each pixel in the targeted color image, determine in the targeted color image with institute State the different pixel of background color image.

2. the method as described in claim 1, it is characterised in that each in targeted color image and background color image The gradient intensity value and gradient direction value of pixel, determine the corresponding second intensity of variation value of each pixel in targeted color image, Including：

The gradient intensity value and gradient direction value of each pixel in targeted color image and background color image, determine mesh Each pixel in coloured image is marked to background color image in the first texture difference value of the pixel of same position, and the back of the body is determined In scape coloured image each pixel to targeted color image the pixel of same position the second texture difference value；

According to the corresponding first texture difference value of each pixel and the second texture difference value, each pixel correspondence is determined The second intensity of variation value.

3. method as claimed in claim 2, it is characterised in that in the targeted color image and the background color image The gradient intensity value and gradient direction value of each pixel meet following equation：

Wherein, x represents the abscissa of the pixel in targeted color image and background color image；Y represent targeted color image and The ordinate of pixel in background color image；(x, y) represents the position where pixel in targeted color image and background color image Put；DT^fb(x, y) represents the picture of the pixel to (x, y) position in background color image of (x, y) position in targeted color image First texture difference value of element；DT^bf(x, y) represents the pixel of (x, y) position in background color image in targeted color figure The second texture difference value of the pixel of (x, y) position as in；S is the image block centered on location of pixels (x, y)；U, v are in S With the coordinate that (x, y) is origin；For in targeted color image (x, y) position pixel gradient intensity value；For mesh In logo image (x, y) position pixel gradient direction value；Represent the pixel in (x, y) position in background color image Gradient intensity value；Represent background color image in (x, y) position pixel gradient direction value.

4. the method as described in claim 1, it is characterised in that background color image is determined according to following manner：

For the multiple image of the continuous acquisition from video capture device, it is determined that the mixed Gaussian of each pixel in per two field picture Model；

The priority of Gaussian Profile in the mixed Gauss model of each pixel in every two field picture, is determined described per frame The background distributions of each pixel in image；

5. method as claimed in claim 4, it is characterised in that according to each pixel in the targeted color image it is corresponding before Scape degree value, determines pixels different from the background color image in the targeted color image, including：

According to the corresponding prospect degree value of each pixel in the targeted color image, the targeted color image is converted into two Value figure；

Determine pixels different from the background color image in the targeted color image：

If it is determined that the number of pixel different from the background color image in the targeted color image is less than the first default threshold Value, redefines a targeted color image, returns to the step for determining the first intensity of variation value and the second intensity of variation value Suddenly, the background color image and according to the targeted color image update.

6. method as claimed in claim 5, it is characterised in that determine in the targeted color image with the background color figure After different pixels, in addition to：

If it is determined that the number of pixel different from the background color image in the targeted color image is preset not less than first Threshold value, extracts what is be made up of in the binary map being converted into by the targeted color image specific pixel according to the number of specific pixel At least one connected region, wherein, specific pixel represents that the targeted color image and the background color image are asynchronous Pixel in the corresponding binary map being converted into by the targeted color image of pixel；

For a connected region, determine the width and height of the connected region minimum enclosed rectangle, according to the width and The height, after it is determined that the connected region meets selection condition, determines the gray level image of the connected region, and will determine Greyscale image transitions into binary map；

7. method as claimed in claim 6, it is characterised in that judge whether the connected region meets choosing according to following manner Take condition：

If the width and the ratio of the height are more than the second predetermined threshold value, it is determined that the connected region meets selection bar Part；

If the ratio of the height and the width is more than the 3rd predetermined threshold value, it is determined that the connected region meets selection bar Part；

If the width and the ratio of the height are not more than the second predetermined threshold value, and the height and the width ratio not More than the 3rd predetermined threshold value, it is determined that the connected region does not meet selection condition.

8. method as claimed in claim 7, it is characterised in that according to the greyscale image transitions by each connected region into two Value figure, determines whether marker connected region, including：

For a connected region, if the width of the connected region minimum enclosed rectangle and the ratio of height are more than described second Predetermined threshold value, then according to by the connected region greyscale image transitions into binary map each pixel gray value vertical Direction project obtaining drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the connection Region is marker connected region, if the crest quantity of drop shadow curve is not more than the 4th threshold value, by by the connected region Greyscale image transitions into the gray value of each pixel of binary map inverted, according to the gray value after reversion in vertical direction Progress, which is projected, obtains drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the connected region It is marker connected region；

For a connected region, the height of the connected region minimum enclosed rectangle and the ratio of width are pre- more than the described 3rd If threshold value, then according to by the connected region greyscale image transitions into binary map each pixel gray value in level side Projected to progress and obtain drop shadow curve, if the crest quantity of statistics drop shadow curve is more than the 4th predetermined threshold value, it is determined that the company Logical region is marker connected region, will be by the connected region if the crest quantity of drop shadow curve is not more than the 4th threshold value Greyscale image transitions into the gray value of each pixel of binary map inverted, according to the gray value after reversion in level side Projected to progress and obtain drop shadow curve, if the crest quantity of drop shadow curve is more than the 4th predetermined threshold value, it is determined that the connected region Domain is marker connected region.

9. a kind of device of image detection, it is characterised in that the device includes：

First degree value determining module, the color for each pixel in targeted color image and background color image Value, determines the corresponding first intensity of variation value of each pixel in targeted color image, and according to targeted color image and background The gradient intensity value and gradient direction value of each pixel in coloured image, determine that each pixel is corresponding in targeted color image Second intensity of variation value, wherein the first intensity of variation value is used to represent in targeted color image that corresponding pixel and background to be color Color image is in intensity of variation of the pixel in color of same position, and the second intensity of variation value is used to represent targeted color figure Intensity of variation of the pixel on texture of corresponding pixel and background color image in same position as in；

Second degree value determining module, for being become according to the corresponding first intensity of variation value of each pixel and described second Change degree value, determine the corresponding 3rd intensity of variation value of each pixel in targeted color image, wherein the 3rd intensity of variation value use In representing the pixel of corresponding pixel and background color image in targeted color image in same position simultaneously in color and texture The degree of upper change；

Prospect degree value determining module, for according to the corresponding 3rd intensity of variation value of each pixel, determining targeted color The corresponding prospect degree value of each pixel in image, wherein the prospect degree value represents corresponding pixel in targeted color image From background color image in the pixel of same position probability simultaneously different in color and texture；

Wherein, each 3rd intensity of variation value meets following equation：

Pixel determining module, for according to the corresponding prospect degree value of each pixel in the targeted color image, it is determined that described The pixel different from the background color image in targeted color image.

10. device as claimed in claim 9, it is characterised in that the first degree value determining module specifically for：

11. device as claimed in claim 9, it is characterised in that described device also includes：

12. device as claimed in claim 11, it is characterised in that the prospect degree value determining module specifically for：

According to the corresponding prospect degree value of each pixel in the targeted color image, the targeted color image is converted into two Value figure；Determine pixels different from the background color image in the targeted color image：

The device also includes：

Module is returned to, for determining that the number of pixels different from the background color image in the targeted color image is less than First predetermined threshold value, redefines a targeted color image, returns and determines the first intensity of variation value and second change The step of degree value, and the background color image according to the targeted color image update.

13. device as claimed in claim 12, it is characterised in that the device also includes：

Judge module, for determining that the number of pixels different from the background color image in the targeted color image is not small In after the first predetermined threshold value, extracted according to the number of specific pixel in the binary map being converted into by the targeted color image by spy At least one connected region of fixation element composition, wherein, the specific pixel represents the targeted color image and the background Pixel in the corresponding binary map being converted into by the targeted color image of the asynchronous pixel of coloured image；For a company Logical region, determines the width and height of the connected region minimum enclosed rectangle, according to the width and the height, it is determined that The connected region meets after selection condition, determines the gray level image of the connected region, and by the greyscale image transitions of determination Into binary map；According to the greyscale image transitions by each connected region into binary map, determine whether marker connected region.