CN104933700B - A kind of method and apparatus carrying out picture material identification - Google Patents
A kind of method and apparatus carrying out picture material identification Download PDFInfo
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- G06V10/243—Aligning, centring, orientation detection or correction of the image by compensating for image skew or non-uniform image deformations
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- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
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Abstract
The disclosure is directed to a kind of method and apparatus for carrying out picture material identification, belong to field of computer technology.The described method includes: carrying out gradient detection processing to images to be recognized, the gradient value of each pixel of the images to be recognized is obtained；First numberical range of each gradient value obtained according to the gradient detection processing and the second value range of preset gray value determine the mapping relations of the gradient value in first numberical range and the gray value within the scope of the second value；Determine the corresponding gray value of gradient value of each pixel respectively according to the mapping relations；According to the corresponding gray value of each pixel determined, the pixel value of each pixel in gradient image is determined, obtain the corresponding gradient image of the images to be recognized, and be based on the gradient image, carry out picture material identification.Using the disclosure, the accuracy of border detection can be improved.
Description
Technical field
The disclosure is directed to field of computer technology, know method for distinguishing and dress especially with respect to a kind of progress picture material
It sets.
Background technique
With the development of computer technology, the purposes of computer is more and more extensive, and function is also stronger and stronger, and people can be with
Picture material identification, such as border detection, character recognition are carried out by computer.Wherein, gradient image is to carry out picture material
Common image in identification.
Vertical gradient operator and horizontal gradient operator can be stored in advance in computer, when computer gets figure to be identified
As after, the gray scale of pixel each in images to be recognized and vertical gradient operator and horizontal gradient operator are subjected to convolution algorithm respectively,
The vertical gradient value and horizontal gradient value of each pixel in images to be recognized are obtained, gradient value can reflect pixel and adjacent pixel
The diversity factor of point.Computer can obtain figure to be identified using vertical gradient value or horizontal gradient value as the pixel value of pixel
The gradient image of picture, and then picture material identification is carried out to images to be recognized according to gradient image.
In implementing the present disclosure, inventor discovery the prior art has at least the following problems:
However, the pixel value range of computer pixel of default when carrying out image procossing is 0~255, if
It was found that the pixel value of pixel less than 0, is then handled as 0, if it find that the pixel value of pixel is greater than 255, then by it
As 255 processing, in this way, when performing image processing, different gradient values may be considered as it is identical, thus, cause to carry out
The accuracy of picture material identification is lower.
Summary of the invention
In order to overcome the problems, such as present in the relevant technologies, present disclose provides a kind of progress picture material know method for distinguishing and
Device.The technical solution is as follows:
According to the first aspect of the embodiments of the present disclosure, a kind of progress picture material knowledge method for distinguishing, the method packet are provided
It includes:
Gradient detection processing is carried out to images to be recognized, obtains the gradient value of each pixel of the images to be recognized；
The of first numberical range of each gradient value obtained according to the gradient detection processing and preset gray value
Two numberical ranges determine that the mapping of the gradient value in first numberical range and the gray value within the scope of the second value is closed
System, in the mapping relations, the corresponding gray value of different gradient values is different；
Determine the corresponding gray value of gradient value of each pixel respectively according to the mapping relations；
According to the corresponding gray value of each pixel determined, the pixel of each pixel in gradient image is determined
Value obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out picture material identification.
Optionally, the first numberical range of each gradient value obtained according to the gradient detection processing, and it is default
Gray value second value range, determine gradient value in first numberical range and the ash within the scope of the second value
The mapping relations of angle value, comprising:
First numberical range of the absolute value of each gradient value obtained according to the gradient detection processing, determines described first
Maximum value and least absolute value in numberical range；
Absolutely according to maximum of the maximum value in the second value range of preset gray value in first numberical range
To value and ratio shared in the difference of least absolute value, the gradient value in first numberical range and second number are determined
It is worth the mapping relations of the gray value in range；
The corresponding gray value of gradient value for determining each pixel respectively according to the mapping relations, comprising:
Determine the corresponding gray value of absolute value of the gradient value of each pixel respectively according to the mapping relations.
Optionally, described that gradient detection processing is carried out to images to be recognized, obtain each pixel of the images to be recognized
The gradient value of point, comprising: vertical gradient operator and horizontal gradient operator according to the pre-stored data carry out gradient to images to be recognized
Detection processing obtains the vertical gradient value and horizontal gradient value of each pixel of the images to be recognized；
First numberical range of each gradient value obtained according to the gradient detection processing and preset gray value
Second value range, determine reflecting for gradient value in first numberical range and the gray value within the scope of the second value
Penetrate relationship, comprising: the first numberical range of each vertical gradient value obtained according to the gradient detection processing and preset ash
The second value range of angle value determines the ash within the scope of the vertical gradient value and the second value in first numberical range
The mapping relations of angle value；According to the third value range for each horizontal gradient value that the gradient detection processing obtains, and it is default
Gray value second value range, determine within the scope of horizontal gradient value within the scope of the third value and the second value
Gray value mapping relations；
The corresponding gray value of gradient value for determining each pixel respectively according to the mapping relations, comprising:
Determine the corresponding gray value of vertical gradient value and each picture of each pixel respectively according to the mapping relations
The corresponding gray value of the horizontal gradient value of vegetarian refreshments.
Optionally, the gradient value is horizontal gradient value or vertical gradient value.
Optionally, described to be based on the gradient image, carry out picture material identification, comprising:
Based on the gradient image, Image Edge-Detection is carried out, the side of the target object in the images to be recognized is obtained
Boundary carries out picture material identification in the boundary of the target object.
According to the second aspect of an embodiment of the present disclosure, a kind of device carrying out picture material identification, described device packet are provided
It includes:
Detection module obtains each picture of the images to be recognized for carrying out gradient detection processing to images to be recognized
The gradient value of vegetarian refreshments；
First determining module, the first numberical range of each gradient value for being obtained according to the gradient detection processing, with
And the second value range of preset gray value, determine the gradient value and the second value range in first numberical range
The mapping relations of interior gray value, in the mapping relations, the corresponding gray value of different gradient values is different；
Second determining module, for determining that the gradient value of each pixel is corresponding respectively according to the mapping relations
Gray value；
Identification module, for determining every in gradient image according to the corresponding gray value of each pixel determined
The pixel value of a pixel obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out image
Content recognition.
Optionally, first determining module, is used for:
First numberical range of the absolute value of each gradient value obtained according to the gradient detection processing, determines described first
Maximum value and least absolute value in numberical range；
Absolutely according to maximum of the maximum value in the second value range of preset gray value in first numberical range
To value and ratio shared in the difference of least absolute value, the gradient value in first numberical range and second number are determined
It is worth the mapping relations of the gray value in range；
Second determining module, is used for:
Determine the corresponding gray value of absolute value of the gradient value of each pixel respectively according to the mapping relations.
Optionally, the detection module, is used for: vertical gradient operator and horizontal gradient operator according to the pre-stored data, right
Images to be recognized carries out gradient detection processing, obtains the vertical gradient value and horizontal ladder of each pixel of the images to be recognized
Angle value；
First determining module, is used for: according to the first number of each vertical gradient value that the gradient detection processing obtains
It is worth the second value range of range and preset gray value, determines the vertical gradient value in first numberical range and institute
State the mapping relations of the gray value within the scope of second value；According to the of each horizontal gradient value that the gradient detection processing obtains
The second value range of three numberical ranges and preset gray value, determines the horizontal gradient value within the scope of the third value
With the mapping relations of the gray value within the scope of the second value；
Second determining module, is used for: determining the vertical ladder of each pixel respectively according to the mapping relations
The corresponding gray value of horizontal gradient value of the corresponding gray value of angle value and each pixel.
Optionally, the gradient value is horizontal gradient value or vertical gradient value.
Optionally, institute's identification module, is used for:
Based on the gradient image, Image Edge-Detection is carried out, the side of the target object in the images to be recognized is obtained
Boundary carries out picture material identification in the boundary of the target object.
According to the third aspect of an embodiment of the present disclosure, a kind of device carrying out picture material identification is provided, comprising:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to:
Gradient detection processing is carried out to images to be recognized, obtains the gradient value of each pixel of the images to be recognized；
The of first numberical range of each gradient value obtained according to the gradient detection processing and preset gray value
Two numberical ranges determine that the mapping of the gradient value in first numberical range and the gray value within the scope of the second value is closed
System, in the mapping relations, the corresponding gray value of different gradient values is different；
Determine the corresponding gray value of gradient value of each pixel respectively according to the mapping relations；
According to the corresponding gray value of each pixel determined, the pixel of each pixel in gradient image is determined
Value obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out picture material identification.
The technical scheme provided by this disclosed embodiment can include the following benefits:
In the embodiment of the present disclosure, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
The of the gradient value of point, the first numberical range of each gradient value obtained according to gradient detection processing and preset gray value
Two numberical ranges determine the mapping relations of the gradient value in the first numberical range and the gray value within the scope of second value, at this
In mapping relations, the corresponding gray value of different gradient values is different, determines the gradient of each pixel respectively according to mapping relations
It is worth corresponding gray value, according to the corresponding gray value of each pixel determined, determines each pixel in gradient image
Pixel value obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification, in this way, due to
The corresponding gray value of different gradient values is different, thus in image procossing, be not in different gradient values is considered as it is identical
The case where, so as to improve the accuracy for carrying out picture material identification.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.In the accompanying drawings:
Fig. 1 is a kind of flow chart for carrying out picture material and knowing method for distinguishing shown according to an exemplary embodiment；
Fig. 2 is a kind of mapping schematic diagram for carrying out picture material identification shown according to an exemplary embodiment；
Fig. 3 is a kind of schematic diagram of device for carrying out picture material identification shown according to an exemplary embodiment；
Fig. 4 is a kind of structural schematic diagram of terminal shown according to an exemplary embodiment.
Through the above attached drawings, it has been shown that the specific embodiment of the disclosure will be hereinafter described in more detail.These attached drawings
It is not intended to limit the scope of this disclosure concept by any means with verbal description, but is by referring to specific embodiments
Those skilled in the art illustrate the concept of the disclosure.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
An exemplary embodiment of the present disclosure provides a kind of progress picture materials to know method for distinguishing, as shown in Figure 1, this method
Process flow may include following step:
In a step 101, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
Gradient value.
In a step 102, the first numberical range of each gradient value obtained according to gradient detection processing and preset ash
The second value range of angle value determines that the mapping of the gradient value in the first numberical range and the gray value within the scope of second value is closed
System, in the mapping relations, the corresponding gray value of different gradient values is different.
In step 103, the corresponding gray value of the gradient value of each pixel is determined respectively according to mapping relations.
At step 104, according to the corresponding gray value of each pixel determined, each pixel in gradient image is determined
The pixel value of point obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification.
In the embodiment of the present disclosure, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
The of the gradient value of point, the first numberical range of each gradient value obtained according to gradient detection processing and preset gray value
Two numberical ranges determine the mapping relations of the gradient value in the first numberical range and the gray value within the scope of second value, at this
In mapping relations, the corresponding gray value of different gradient values is different, determines the gradient of each pixel respectively according to mapping relations
It is worth corresponding gray value, according to the corresponding gray value of each pixel determined, determines each pixel in gradient image
Pixel value obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification, in this way, due to
The corresponding gray value of different gradient values is different, thus in image procossing, be not in different gradient values is considered as it is identical
The case where, so as to improve the accuracy for carrying out picture material identification.
Disclosure another exemplary embodiment provides a kind of progress picture material knowledge method for distinguishing, and this method can be used for
In terminal, wherein terminal can be the terminal with image identification function, such as mobile phone or tablet computer mobile terminal.It is described
Application program with picture material identification function can be installed, the terminal may include input unit, described in terminal
Input unit can be camera, be also possible to scanner etc., and terminal can obtain images to be recognized by input unit；It is described
Terminal may include processor, and the processor can carry out identifying processing according to the images to be recognized got, as edge is examined
Survey or character recognition etc.；The terminal can also include display unit, and the display unit can be shown single with liquid crystal display
The information that member can be obtained with video-stream processor by identifying processing.In addition, the terminal can also include memory, sensor,
The components such as voicefrequency circuit and power supply.
Below in conjunction with embodiment, process flow shown in FIG. 1 is described in detail, content can be such that
In a step 101, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
Gradient value.
In an implementation, user can install the application program with picture material identification function in terminal, and user can lead to
The information for crossing object (i.e. target object) included in application program identification image, as identified the bank card on bank card
Number.When user wishes to identify target object, user can open the application program in terminal, and terminal can open input equipment
(such as camera), and detection zone is shown in screen, user can be with the positions of mobile terminal, so that terminal is available includes
There is the image (i.e. images to be recognized) of target object.After terminal obtains images to be recognized, it can be calculated by sobel border detection
Method carries out gradient detection processing to images to be recognized.Terminal can determine the gray value of each pixel in images to be recognized, so
The operator in the gray value of each pixel and sobel algorithm can be subjected to convolution algorithm afterwards, obtain images to be recognized
Each pixel gradient value.In sobel algorithm include vertical gradient operator and horizontal gradient operator, terminal can determine to
The vertical gradient value or horizontal gradient value for identifying each pixel in image, can also determine each pixel in images to be recognized
Vertical gradient value and horizontal gradient value, corresponding processing mode can have following two:
Mode one, vertical gradient operator according to the pre-stored data and horizontal gradient operator carry out gradient to images to be recognized
Detection processing obtains the vertical gradient value and horizontal gradient value of each pixel of images to be recognized.
In an implementation, vertical gradient operator and horizontal gradient operator in sobel algorithm can be stored in advance in terminal, it is right
In to any pixel point (x, y) in images to be recognized, terminal can use vertical gradient operator and horizontal gradient operator pair respectively
Pixel (x, y) carries out convolution algorithm, obtains the vertical gradient value and horizontal gradient value of pixel (x, y).
Vertical gradient operator and horizontal gradient operator in sobel algorithm is as shown in the table:
For any pixel point (x, y) in images to be recognized, (x, y) pixel adjacent thereto can be indicated are as follows:
| (x-1, y+1) | (x, y+1) | (x+1, y+1) |
| (x-1, y) | (x, y) | (x+1, y) |
| (x-1, y-1) | (x, y-1) | (x+1, y-1) |
Pixel (x, y) corresponding gray value in images to be recognized can be expressed as f (x, y), and terminal can pass through volume
Product calculates, and to obtain the vertical gradient value and horizontal gradient value of pixel (x, y), specific calculating process be can be such that
Vertical gradient value:
Gy=1*f (x-1, y+1)+2*f (x, y+1)+1*f (x+1, y+1)+0*f (x-1, y)+0*f (x, y)+0*f (x+1,
Y)+(- 1) * f (x-1, y-1)+(- 2) * f (x, y-1)+(- 1) * f (x+1, y-1)=[f (x-1, y+1)+2f (x, y+1)+f (x+
1,y+1)]-[f(x-1,y-1)+2*f(x,y-1)+f(x+1,y-1)]
Horizontal vertical ladder angle value:
Gx=(- 1) * f (x-1, y+1)+0*f (x, y+1)+1*f (x+1, y+1)+(- 2) * f (x-1, y)+0*f (x, y)+2*
F (x+1, y)+(- 1) * f (x-1, y-1)+0*f (x, y-1)+1*f (x+1, y-1)=[f (x+1, y+1)+2*f (x+1, y)+f (x+
1,y-1)]-[f(x-1,y+1)+2*f(x-1,y)+f(x-1,y-1)]
Mode two, vertical gradient operator according to the pre-stored data or horizontal gradient operator carry out gradient to images to be recognized
Detection processing obtains the vertical gradient value or horizontal gradient value of each pixel of images to be recognized.
In an implementation, it is based on calculation method identical with above-mentioned calculating vertical gradient value and/or horizontal gradient value, terminal can
Only to calculate the vertical gradient value of each pixel of images to be recognized, or only calculate each pixel of images to be recognized
Horizontal gradient value repeats no more.
In a step 102, the first numberical range of each gradient value obtained according to gradient detection processing and preset ash
The second value range of angle value determines that the mapping of the gradient value in the first numberical range and the gray value within the scope of second value is closed
System, in the mapping relations, the corresponding gray value of different gradient values is different.
In an implementation, terminal obtains each ladder that in images to be recognized after the gradient value of each pixel, can be determined
The numberical range (i.e. the first numberical range) of angle value, and can store range (the i.e. second value model of preset gray value
Enclose), second value may range from 0~255, and then terminal can determine gradient value and second value in the first numberical range
The mapping relations of gray value in range.
For example, terminal determines that the first numberical range is -100~1000, any gradient value a in the first numberical range and
The mapping relations of gray value in two numberical ranges can be with are as follows:
Gray value a '=[a- (- 100)] * 255/ [1000- (- 100)]=(a+100) * 255/1100 after mapping
Optionally, it can first determine the absolute value of each gradient value, then determine mapping relations, correspondingly, the place of step 102
Reason process can be such that the first numberical range of the absolute value of each gradient value obtained according to gradient detection processing, determine first
Maximum value and least absolute value in numberical range；Existed according to the maximum value in the second value range of preset gray value
Maximum value and ratio shared in the difference of least absolute value in first numberical range, determine in the first numberical range
The mapping relations of gray value within the scope of gradient value and second value.
In an implementation, terminal obtains to determine each pixel in images to be recognized after the gradient value of each pixel
Gradient value absolute value, and then determine these absolute values in maximum value and least absolute value, thus obtain first number
It is worth range, can store the range (i.e. second value range) of preset gray value in terminal, second value may range from 0~
255, for 0~255, terminal can determine the difference of 255 maximum value and least absolute value in the first numberical range
Shared ratio in value, and then terminal can determine the gray value in gradient value and 0~255 range in the first numberical range
Mapping relations.
For example, terminal can determine in the absolute value of the gradient value of each pixel, maximum value 1000 is minimum exhausted
It is 100 to value, i.e. the first numberical range is 100~1000, in any gradient value a and 0~255 range in the first numberical range
The mapping relations of gray value can be with are as follows:
Gray value a '=(a-100) * 255/ (1000-100) after mapping
Optionally, the feelings of the vertical gradient value for the above-mentioned each pixel for obtaining images to be recognized and horizontal gradient value
Condition, correspondingly, the treatment process of step 102 can be such that the first of each vertical gradient value obtained according to gradient detection processing
The second value range of numberical range and preset gray value, determines the vertical gradient value in the first numberical range and second
The mapping relations of gray value in numberical range；According to the third value model for each horizontal gradient value that gradient detection processing obtains
It encloses and the second value range of preset gray value, determines the horizontal gradient value and second value model within the scope of third value
The mapping relations of gray value in enclosing.
It in an implementation, can after terminal obtains the vertical gradient value and horizontal gradient value of each pixel of images to be recognized
In obtained vertical gradient value, to determine the maximum value and minimum value in vertical gradient value, to obtain vertical gradient value
Numberical range (i.e. the first numberical range).Terminal can store the range (i.e. second value range) of preset gray value, and second
Numberical range can be 0~255, and then terminal can determine vertical gradient value and second value range in the first numberical range
The mapping relations of interior gray value.In addition, terminal can also first determine the absolute value of vertical gradient value, vertical gradient is then determined
First numberical range of the absolute value of value and maximum value and least absolute value in the first numberical range, according to default
Gray value second value range in maximum value and least absolute value of the maximum value in the first numberical range difference
Shared ratio in value determines that the mapping of the gray value within the scope of vertical gradient value and second value in the first numberical range is closed
System, specific treatment process is similar with above-mentioned treatment process, repeats no more.
Terminal can also determine the maximum value and minimum value in horizontal gradient value in obtained horizontal gradient value, thus
Obtain the numberical range (i.e. third value range) of horizontal gradient value.Terminal can store the range (i.e. of preset gray value
Two numberical ranges), second value may range from 0~255, and then terminal can determine the horizontal gradient within the scope of third value
The mapping relations of value and the gray value within the scope of second value.In addition, terminal can also first determine the absolute value of horizontal gradient value,
Then the third value range for determining the absolute value of horizontal gradient value, determines the maximum value and minimum in third value range
Absolute value, according to maximum value of the maximum value in the second value range of preset gray value in third value range with
Shared ratio in the difference of least absolute value determines within the scope of the horizontal gradient value and second value within the scope of third value
The mapping relations of gray value, specific treatment process is similar with above-mentioned treatment process, repeats no more.
In step 103, the corresponding gray value of the gradient value of each pixel is determined respectively according to mapping relations.
In an implementation, terminal determines the mapping of the gradient value in the first numberical range and the gray value within the scope of second value
After relationship, the gradient value of each pixel can be brought into the mapping relations determined, obtain the gradient value of each pixel
Corresponding gray value.For example, terminal determines that the first numberical range is -100~1000, any gradient value in the first numberical range
The mapping relations of gray value within the scope of a and second value can be with are as follows: gray value a '=[a- (- 100)] * 255/ after mapping
[1000- (- 100)]=(a+100) * 255/1100, pixel (x1,y1) gradient value be 500, then pixel (x1,y1) ladder
The corresponding gray value of angle value is (500+100) * 255/1100=139.The corresponding gray value of the gradient value of each pixel is general
For integer, the case where for non-integer is calculated, each pixel can be obtained using the modes such as rounding up or being rounded
The corresponding gray value of gradient value.
Optionally, the case where the absolute value of the gradient value of pixel each for above-mentioned determination, correspondingly, step 103
Treatment process can be such that determines the corresponding gray value of the absolute value of the gradient value of each pixel according to mapping relations respectively.
In an implementation, terminal determines the mapping of the gradient value in the first numberical range and the gray value within the scope of second value
After relationship, the absolute value of the gradient value of each pixel can be brought into the formula for the mapping relations determined, be obtained each
The corresponding gray value of the gradient value of pixel.For example, terminal determines that the first numberical range is 100~1000, the first numberical range
The mapping relations of interior any gradient value a and the gray value within the scope of second value can be with are as follows: gray value a '=(a- after mapping
100) * 255/ (1000-100), pixel (x1,y1) gradient value be -150, then pixel (x1,y1) gradient value it is absolute
Being worth corresponding gray value is (150-100) * 255/ (1000-100)=14, as shown in Figure 2.The gradient value of each pixel is corresponding
Gray value be generally integer, the case where for non-integer is calculated, can be obtained using the modes such as rounding up or being rounded
To the corresponding gray value of gradient value of each pixel.
Optionally, for the gray value within the scope of the vertical gradient value and second value in above-mentioned the first numberical range of determination
Mapping relations, and determine third value within the scope of horizontal gradient value and second value within the scope of gray value mapping close
The case where being, correspondingly, the treatment process of step 103 can be such that determines hanging down for each pixel according to mapping relations respectively
The corresponding gray value of horizontal gradient value of the corresponding gray value of vertical ladder angle value and each pixel.
In an implementation, terminal determines the gray value within the scope of vertical gradient value and second value in the first numberical range
After mapping relations, the vertical gradient value of each pixel can be brought into the formula for the mapping relations determined, be obtained each
The corresponding gray value of the vertical gradient value of pixel.Terminal can also determine the horizontal gradient value and within the scope of third value
After the mapping relations of gray value in two numberical ranges into, the horizontal gradient value of each pixel can be brought to reflecting of determining
It penetrates in the formula of relationship, obtains the corresponding gray value of horizontal gradient value of each pixel.
At step 104, according to the corresponding gray value of each pixel determined, each pixel in gradient image is determined
The pixel value of point obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification.
In an implementation, it after terminal determines the corresponding gray value of the gradient value of each pixel, can determine in gradient image
The pixel value of each pixel, so that the corresponding gradient image of images to be recognized is obtained, and then terminal can be based on gradient image,
Picture material identification is carried out, for example, terminal can be based on gradient image, object included in image is identified, determines object
Contour line.
The case where vertical gradient value or horizontal gradient value of pixel each for determination, terminal can be by each pixels
The corresponding gray value of vertical gradient value, as the pixel value of pixel each in gradient image, alternatively, terminal can will be each
The corresponding gray value of the horizontal gradient value of pixel, the pixel value as pixel each in gradient image.Terminal can basis
The pixel value of each pixel in gradient image obtains the corresponding gradient image of images to be recognized.
The case where vertical gradient value and horizontal gradient value of pixel each for determination, for appointing in images to be recognized
One pixel, the corresponding gray scale of the corresponding sum of the grayscale values horizontal gradient value of the vertical gradient value of the available pixel of terminal
Value, then can calculate square gray value corresponding with horizontal gradient value of the corresponding gray value of vertical gradient value square and
Value, then to this and value progress extracting operation, the corresponding pixel value of the pixel is obtained, and then obtain the corresponding ladder of images to be recognized
Spend image.
Optionally, it is also based on gradient image and carries out Image Edge-Detection, corresponding treatment process, which can be such that, to be based on
Gradient image carries out Image Edge-Detection, the boundary of the target object in images to be recognized is obtained, on the boundary of target object
It is interior, carry out picture material identification.
In an implementation, after terminal obtains the corresponding gradient image of images to be recognized, image can be carried out in gradient image
Edge detection, obtains the boundary of the target object in images to be recognized, and terminal can carry out image in the boundary of target object
Content recognition.For example, target object can be bank card, then terminal can obtain the side of bank card by Image Edge-Detection
Boundary carries out picture material identification, to identify the card number on bank card then in the boundary of bank card.
In the embodiment of the present disclosure, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
The of the gradient value of point, the first numberical range of each gradient value obtained according to gradient detection processing and preset gray value
Two numberical ranges determine the mapping relations of the gradient value in the first numberical range and the gray value within the scope of second value, at this
In mapping relations, the corresponding gray value of different gradient values is different, determines the gradient of each pixel respectively according to mapping relations
It is worth corresponding gray value, according to the corresponding gray value of each pixel determined, determines each pixel in gradient image
Pixel value obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification, in this way, due to
The corresponding gray value of different gradient values is different, thus in image procossing, be not in different gradient values is considered as it is identical
The case where, so as to improve the accuracy for carrying out picture material identification.
Disclosure another exemplary embodiment provides a kind of device for carrying out picture material identification, as shown in figure 3, the dress
Setting includes: detection module 310, the first determining module 320, the second determining module 330 and identification module 340.
Detection module 310 obtains each of described images to be recognized for carrying out gradient detection processing to images to be recognized
The gradient value of pixel；
First determining module 320, the first numberical range of each gradient value for being obtained according to the gradient detection processing,
And the second value range of preset gray value, determine the gradient value in first numberical range and the second value model
The mapping relations of gray value in enclosing, in the mapping relations, the corresponding gray value of different gradient values is different；
Second determining module 330, for determining the gradient value pair of each pixel respectively according to the mapping relations
The gray value answered；
Identification module 340, for determining in gradient image according to the corresponding gray value of each pixel determined
The pixel value of each pixel obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out figure
As content recognition.
Optionally, first determining module 320, is used for:
First numberical range of the absolute value of each gradient value obtained according to the gradient detection processing, determines described first
Maximum value and least absolute value in numberical range；
Absolutely according to maximum of the maximum value in the second value range of preset gray value in first numberical range
To value and ratio shared in the difference of least absolute value, the gradient value in first numberical range and second number are determined
It is worth the mapping relations of the gray value in range；
Second determining module 330, is used for:
Determine the corresponding gray value of absolute value of the gradient value of each pixel respectively according to the mapping relations.
Optionally, the detection module 310, is used for: vertical gradient operator and horizontal gradient operator according to the pre-stored data,
Gradient detection processing is carried out to images to be recognized, obtains the vertical gradient value and level of each pixel of the images to be recognized
Gradient value；
First determining module 320, is used for: according to the first of each vertical gradient value that the gradient detection processing obtains
The second value range of numberical range and preset gray value, determine vertical gradient value in first numberical range with
The mapping relations of gray value within the scope of the second value；Each horizontal gradient value obtained according to the gradient detection processing
The second value range of third value range and preset gray value, determines the horizontal gradient within the scope of the third value
The mapping relations of value and the gray value within the scope of the second value；
Second determining module 330, is used for: determining the vertical of each pixel respectively according to the mapping relations
The corresponding gray value of horizontal gradient value of the corresponding gray value of gradient value and each pixel.
Optionally, the gradient value is horizontal gradient value or vertical gradient value.
Optionally, institute's identification module 340, is used for:
Based on the gradient image, Image Edge-Detection is carried out, the side of the target object in the images to be recognized is obtained
Boundary carries out picture material identification in the boundary of the target object.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
In the embodiment of the present disclosure, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
The of the gradient value of point, the first numberical range of each gradient value obtained according to gradient detection processing and preset gray value
Two numberical ranges determine the mapping relations of the gradient value in the first numberical range and the gray value within the scope of second value, at this
In mapping relations, the corresponding gray value of different gradient values is different, determines the gradient of each pixel respectively according to mapping relations
It is worth corresponding gray value, according to the corresponding gray value of each pixel determined, determines each pixel in gradient image
Pixel value obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification, in this way, due to
The corresponding gray value of different gradient values is different, thus in image procossing, be not in different gradient values is considered as it is identical
The case where, so as to improve the accuracy for carrying out picture material identification.
It should be understood that the device provided by the above embodiment for carrying out picture material identification is carrying out picture material identification
When, only the example of the division of the above functional modules, in practical application, it can according to need and divide above-mentioned function
With being completed by different functional modules, i.e., the internal structure of equipment is divided into different functional modules, to complete above description
All or part of function.In addition, the device provided by the above embodiment for carrying out picture material identification and progress picture material
The embodiment of the method for identification belongs to same design, and specific implementation process is detailed in embodiment of the method, and which is not described herein again.
The another exemplary embodiment of the disclosure provides a kind of structural schematic diagram of terminal.The terminal can be mobile phone etc..
Referring to Fig. 4, terminal 800 may include following one or more components: processing component 802, memory 804, power supply
Component 806, multimedia component 808, audio component 810, the interface 812 of input/output (I/O), sensor module 814, and
Communication component 816.
The integrated operation of the usual controlling terminal 800 of processing component 802, such as with display, telephone call, data communication, phase
Machine operation and record operate associated operation.Processing element 802 may include that one or more processors 820 refer to execute
It enables, to perform all or part of the steps of the methods described above.In addition, processing component 802 may include one or more modules, just
Interaction between processing component 802 and other assemblies.For example, processing component 802 may include multi-media module, it is more to facilitate
Interaction between media component 808 and processing component 802.
Memory 804 is configured as storing various types of data to support the operation in terminal 800.These data are shown
Example includes the instruction of any application or method for operating in terminal 800, contact data, and telephone book data disappears
Breath, picture, video etc..Memory 804 can be by any kind of volatibility or non-volatile memory device or their group
It closes and realizes, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM) is erasable to compile
Journey read-only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, flash
Device, disk or CD.
Electric power assembly 806 provides electric power for the various assemblies of terminal 800.Electric power assembly 806 may include power management system
System, one or more power supplys and other with for audio output apparatus 800 generate, manage, and distribute the associated component of electric power.
Multimedia component 808 includes the screen of one output interface of offer between the terminal 800 and user.One
In a little embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, screen
Curtain may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or more touch sensings
Device is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding action
Boundary, but also detect duration and pressure associated with the touch or slide operation.In some embodiments, more matchmakers
Body component 808 includes a front camera and/or rear camera.When terminal 800 is in operation mode, such as screening-mode or
When video mode, front camera and/or rear camera can receive external multi-medium data.Each front camera and
Rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 810 is configured as output and/or input audio signal.For example, audio component 810 includes a Mike
Wind (MIC), when audio output apparatus 800 is in operation mode, when such as call mode, recording mode, and voice recognition mode, wheat
Gram wind is configured as receiving external audio signal.The received audio signal can be further stored in memory 804 or warp
It is sent by communication component 816.
I/O interface 812 provides interface between processing component 802 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and lock
Determine button.
Sensor module 814 includes one or more sensors, and the state for providing various aspects for terminal 800 is commented
Estimate.For example, sensor module 814 can detecte the state that opens/closes of terminal 800, and the relative positioning of component, for example, it is described
Component is the display and keypad of terminal 800, and sensor module 814 can also detect 800 1 components of terminal 800 or terminal
Position change, the existence or non-existence that user contacts with terminal 800,800 orientation of terminal or acceleration/deceleration and terminal 800
Temperature change.Sensor module 814 may include proximity sensor, be configured to detect without any physical contact
Presence of nearby objects.Sensor module 814 can also include optical sensor, such as CMOS or ccd image sensor, at
As being used in application.In some embodiments, which can also include acceleration transducer, gyro sensors
Device, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 816 is configured to facilitate the communication of wired or wireless way between terminal 800 and other equipment.Terminal
800 can access the wireless network based on communication standard, such as WiFi, 2G or 3G or their combination.In an exemplary implementation
In example, communication component 816 receives broadcast singal or broadcast related information from external broadcasting management system via broadcast channel.
In one exemplary embodiment, the communication component 816 further includes near-field communication (NFC) module, to promote short range communication.Example
Such as, NFC module can be based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band (UWB) technology,
Bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, terminal 800 can be believed by one or more application specific integrated circuit (ASIC), number
Number processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array
(FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for executing the above method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 804 of instruction, above-metioned instruction can be executed by the processor 820 of terminal 800 to complete the above method.For example,
The non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk
With optical data storage devices etc..
A kind of non-transitorycomputer readable storage medium, when the instruction in the storage medium is held by the processor of terminal
When row, enable the terminal to execute a kind of progress picture material knowledge method for distinguishing, this method comprises:
Gradient detection processing is carried out to images to be recognized, obtains the gradient value of each pixel of the images to be recognized；
The of first numberical range of each gradient value obtained according to the gradient detection processing and preset gray value
Two numberical ranges determine that the mapping of the gradient value in first numberical range and the gray value within the scope of the second value is closed
System, in the mapping relations, the corresponding gray value of different gradient values is different；
Determine the corresponding gray value of gradient value of each pixel respectively according to the mapping relations；
According to the corresponding gray value of each pixel determined, the pixel of each pixel in gradient image is determined
Value obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out picture material identification.
Optionally, the first numberical range of each gradient value obtained according to the gradient detection processing, and it is default
Gray value second value range, determine gradient value in first numberical range and the ash within the scope of the second value
The mapping relations of angle value, comprising:
First numberical range of the absolute value of each gradient value obtained according to the gradient detection processing, determines described first
Maximum value and least absolute value in numberical range；
Absolutely according to maximum of the maximum value in the second value range of preset gray value in first numberical range
To value and ratio shared in the difference of least absolute value, the gradient value in first numberical range and second number are determined
It is worth the mapping relations of the gray value in range；
The corresponding gray value of gradient value for determining each pixel respectively according to the mapping relations, comprising:
Determine the corresponding gray value of absolute value of the gradient value of each pixel respectively according to the mapping relations.
Optionally, described that gradient detection processing is carried out to images to be recognized, obtain each pixel of the images to be recognized
The gradient value of point, comprising: vertical gradient operator and horizontal gradient operator according to the pre-stored data carry out gradient to images to be recognized
Detection processing obtains the vertical gradient value and horizontal gradient value of each pixel of the images to be recognized；
First numberical range of each gradient value obtained according to the gradient detection processing and preset gray value
Second value range, determine reflecting for gradient value in first numberical range and the gray value within the scope of the second value
Penetrate relationship, comprising: the first numberical range of each vertical gradient value obtained according to the gradient detection processing and preset ash
The second value range of angle value determines the ash within the scope of the vertical gradient value and the second value in first numberical range
The mapping relations of angle value；According to the third value range for each horizontal gradient value that the gradient detection processing obtains, and it is default
Gray value second value range, determine within the scope of horizontal gradient value within the scope of the third value and the second value
Gray value mapping relations；
The corresponding gray value of gradient value for determining each pixel respectively according to the mapping relations, comprising:
Determine the corresponding gray value of vertical gradient value and each picture of each pixel respectively according to the mapping relations
The corresponding gray value of the horizontal gradient value of vegetarian refreshments.
Optionally, the gradient value is horizontal gradient value or vertical gradient value.
Optionally, described to be based on the gradient image, carry out picture material identification, comprising:
Based on the gradient image, Image Edge-Detection is carried out, the side of the target object in the images to be recognized is obtained
Boundary carries out picture material identification in the boundary of the target object.
In the embodiment of the present disclosure, gradient detection processing is carried out to images to be recognized, obtains each pixel of images to be recognized
The of the gradient value of point, the first numberical range of each gradient value obtained according to gradient detection processing and preset gray value
Two numberical ranges determine the mapping relations of the gradient value in the first numberical range and the gray value within the scope of second value, at this
In mapping relations, the corresponding gray value of different gradient values is different, determines the gradient of each pixel respectively according to mapping relations
It is worth corresponding gray value, according to the corresponding gray value of each pixel determined, determines each pixel in gradient image
Pixel value obtains the corresponding gradient image of images to be recognized, and is based on gradient image, carries out picture material identification, in this way, due to
The corresponding gray value of different gradient values is different, thus in image procossing, be not in different gradient values is considered as it is identical
The case where, so as to improve the accuracy for carrying out picture material identification.
Those skilled in the art will readily occur to its of the disclosure after considering specification and practicing disclosure disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claim is pointed out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the accompanying claims.
Claims (6)
1. a kind of progress picture material knows method for distinguishing, which is characterized in that the described method includes:
Vertical gradient operator and horizontal gradient operator according to the pre-stored data carry out gradient detection processing to images to be recognized, obtain
To the vertical gradient value and horizontal gradient value of each pixel of the images to be recognized；
First numberical range of the absolute value of each vertical gradient value obtained according to the gradient detection processing, determines described first
The maximum value and least absolute value of vertical gradient value in numberical range；Each level obtained according to the gradient detection processing
The third value range of the absolute value of gradient value determines in the third value range maximum value of horizontal gradient value and most
Small absolute value；
According to the maximum value in the second value range of preset gray value in first numberical range vertical gradient value
Shared ratio in the difference of maximum value and least absolute value, determine vertical gradient value in first numberical range with
The mapping relations of gray value within the scope of the second value, according to the maximum value in the second value range of preset gray value
The ratio shared in the maximum value of horizontal gradient value and the difference of least absolute value in the third value range, determines
The mapping relations of the gray value within the scope of horizontal gradient value and the second value within the scope of the third value, reflect described
It penetrates in relationship, the corresponding gray value of different gradient values is different；
The corresponding gray value of vertical gradient value of each pixel and described every is determined respectively according to the mapping relations
The corresponding gray value of the horizontal gradient value of a pixel；
According to the corresponding gray value of each pixel determined, the pixel value of each pixel in gradient image is determined,
The corresponding gradient image of the images to be recognized is obtained, and is based on the gradient image, carries out picture material identification.
2. the method according to claim 1, wherein the gradient value is horizontal gradient value or vertical gradient value.
3. carrying out picture material knowledge the method according to claim 1, wherein described be based on the gradient image
Not, comprising:
Based on the gradient image, Image Edge-Detection is carried out, the boundary of the target object in the images to be recognized is obtained,
In the boundary of the target object, picture material identification is carried out.
4. a kind of device for carrying out picture material identification, which is characterized in that described device includes:
Detection module is used for vertical gradient operator according to the pre-stored data and horizontal gradient operator, carries out ladder to images to be recognized
Detection processing is spent, the vertical gradient value and horizontal gradient value of each pixel of the images to be recognized are obtained；
First determining module, the first numerical value of the absolute value of each vertical gradient value for being obtained according to the gradient detection processing
Range determines the maximum value and least absolute value of vertical gradient value in first numberical range；It is examined according to the gradient
The third value range of the absolute value for each horizontal gradient value that survey is handled determines horizontal gradient in the third value range
The maximum value and least absolute value of value；According to the maximum value in the second value range of preset gray value described first
Ratio shared in the maximum value of vertical gradient value and the difference of least absolute value in numberical range determines first number
It is worth the mapping relations of the gray value within the scope of the vertical gradient value and the second value in range, according to preset gray value
The maximum value and least absolute value of maximum value horizontal gradient value in the third value range in second value range
Difference in shared ratio, determine the ash within the scope of the horizontal gradient value and the second value within the scope of the third value
The mapping relations of angle value, in the mapping relations, the corresponding gray value of different gradient values is different；
Second determining module, for determining that the vertical gradient value of each pixel is corresponding respectively according to the mapping relations
The corresponding gray value of horizontal gradient value of gray value and each pixel；
Identification module, for determining each picture in gradient image according to the corresponding gray value of each pixel determined
The pixel value of vegetarian refreshments obtains the corresponding gradient image of the images to be recognized, and is based on the gradient image, carries out picture material
Identification.
5. device according to claim 4, which is characterized in that the gradient value is horizontal gradient value or vertical gradient value.
6. device according to claim 4, which is characterized in that institute's identification module is used for:
Based on the gradient image, Image Edge-Detection is carried out, the boundary of the target object in the images to be recognized is obtained,
In the boundary of the target object, picture material identification is carried out.
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| CN107371001B (en) * | 2017-08-25 | 2018-07-20 | 北京中都格罗唯视物流有限公司 | A kind of heavy truck real-time monitoring system |
| CN107392942B (en) * | 2017-08-28 | 2018-06-05 | 广州文冠信息科技有限公司 | Human body target real-time analyzer |
| CN107563321B (en) * | 2017-08-28 | 2018-07-13 | 深圳市奥丝卡生物科技有限公司 | A kind of human body target real-time analysis method |
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