CN108846319A - Iris image Enhancement Method, device, equipment and storage medium based on histogram - Google Patents
Iris image Enhancement Method, device, equipment and storage medium based on histogram Download PDFInfo
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Abstract
The invention discloses a kind of iris image Enhancement Method, device, equipment and storage medium based on histogram.The iris image Enhancement Method based on histogram includes：Obtain iris image collection；The contrast of iris image is calculated, same user identifier is based on, iris image is ranked up according to contrast descending sequence, obtains the corresponding initial iris sequence of each user identifier；The iris image for sequentially obtaining preset quantity from initial iris sequence based on each user identifier, forms initial iris collection；Local enhancement processing is carried out to initial iris image using adaptive histogram equalization algorithm, obtains the first enhancing iris image collection；Processing is sharpened using Laplace operator to the first enhancing iris image, obtains the second enhancing iris image collection.The iris image Enhancement Method based on histogram not only increases the overall contrast of initial iris image, enhances interior details, and inhibits the noise amplified during enhancing, has preferable reinforcing effect, improves the recognition accuracy of iris image.
Description
Technical field
The present invention relates to field of image processing more particularly to a kind of iris image Enhancement Method based on histogram, device,
Equipment and storage medium.
Background technique
Iris as a kind of important identity authentication feature, have uniqueness, stability, can collectivity and non-infringement property etc.
Feature.In iris authentication system, it is often necessary to the higher iris image of clarity as training set, but due to acquire equipment
Limitation and the acquisition factors such as environmental change influence, can all cause the iris image quality of acquisition bad, as contrast is low and
The problems such as noise jamming, can all influence highlighting for iris texture characteristic, and then influence the clarity and identification of iris image training set
Efficiency.In order to improve the accuracy rate of identification, generally require to carry out enhancing processing to iris image, to highlight the texture spy of image
Sign.It is at present generally only the contrast progress overall dynamics adjustment to collected iris image, however what process was so handled
Accuracy rate of the iris image in identifying system be not still high.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide a kind of iris image Enhancement Method based on histogram, dress
It sets, equipment and storage medium, to solve the problems, such as that iris image recognition accuracy is not high.
A kind of iris image Enhancement Method based on histogram, including：
Iris image collection is obtained, the iris image collection includes iris image, and the iris image includes user identifier；
The contrast for calculating the iris image that the iris image is concentrated, according to the descending sequence of contrast to iris
The corresponding iris image of each user identifier is ranked up in image set, obtains the corresponding initial iris sequence of each user identifier
Column；
The sequence descending according to contrast obtains present count from the corresponding initial iris sequence of each user identifier
The iris image of amount forms initial iris collection；
Local increasing is carried out using the initial iris image that adaptive histogram equalization algorithm concentrates the initial iris
Strength reason, obtains the first enhancing iris image collection；
The first enhancing iris image that the first enhancing iris image is concentrated is sharpened using Laplace operator
Processing, obtains the second enhancing iris image collection.
A kind of iris image enhancement device based on histogram, including：
Iris image collection obtains module, and for obtaining iris image collection, the iris image collection includes iris image, described
Iris image includes user identifier；
Iris retrieval module, for calculating the contrast for the iris image that the iris image is concentrated, and according to right
The sequence more descending than degree concentrates the corresponding iris image of each user identifier to be ranked up iris image, obtains each use
Family identifies corresponding initial iris sequence；
Initial iris collection obtains module, for from the corresponding initial iris sequence of each user identifier according to contrast by
The iris image that small sequence obtains preset quantity is arrived greatly, forms initial iris collection；
First enhancing iris image collection obtains module, for using adaptive histogram equalization algorithm to the initial rainbow
The initial iris image that film is concentrated carries out local enhancement processing, obtains the first enhancing iris image collection；
Second enhancing iris image collection obtains module, the first enhancing rainbow for concentrating to the first enhancing iris image
Film image is sharpened processing using Laplace operator, obtains the second enhancing iris image collection.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize the above-mentioned iris figure based on histogram when executing the computer program
The step of image intensifying method.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
Calculation machine program realizes the step of above-mentioned iris image Enhancement Method based on histogram when being executed by processor.
Above-mentioned iris image Enhancement Method, device, equipment and storage medium based on histogram, first acquisition iris image
Collection calculates contrast to the corresponding iris image of same user identifier that image iris is concentrated, and descending according to contrast
Sequence be ranked up, obtain the corresponding initial iris sequence of each user identifier, using contrast size as iris image select
The standard taken is handled convenient for the subsequent biggish iris image of contrast of therefrom selecting.Then, according to each user identifier from
The iris image that preset quantity is sequentially obtained in initial iris sequence, forms initial iris collection, so as to it is subsequent to the iris collection into
Row processing, is reduced some redundant operations, accelerates the real-time of image procossing, next, being calculated using adaptive histogram equalization
Method carries out local enhancement processing to the initial iris image that initial iris is concentrated, and not only extends the ash of initial iris image pixel
The dynamic range of angle value, and local contrast has also obtained adaptive adjustment, and overall contrast effectively improves, and enhances
Interior details.Finally, being sharpened processing to enhanced iris image, the noise amplified during enhancing is not only inhibited,
And whole picture iris image edge details feature is reinforced, and has preferable reinforcing effect, and the identification for improving iris image is quasi-
True rate.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the application scenario diagram of the iris image Enhancement Method in one embodiment of the invention based on histogram；
Fig. 2 is a flow chart of the iris image Enhancement Method in the embodiment of the present invention based on histogram；
Fig. 3 is a flow chart of a specific embodiment of step S10 in Fig. 2；
Fig. 4 is a flow chart of a specific embodiment of step S20 in Fig. 2；
Fig. 5 is a flow chart of a specific embodiment of step S50 in Fig. 2；
Fig. 6 (a) is the exemplary diagram of an initial iris image in the embodiment of the present invention；
Fig. 6 (b) is the exemplary diagram of one second enhancing iris image in the embodiment of the present invention；
Fig. 7 is a schematic diagram of the iris image enhancement device in the embodiment of the present invention based on histogram；
Fig. 8 is a schematic diagram of computer equipment in the embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Iris image Enhancement Method provided by the present application based on histogram, can apply in computer equipment or system
In, for carrying out enhancing processing to iris image, to solve the problems, such as that iris image recognition accuracy is not high.Wherein, computer
Equipment can be, but not limited to various personal computers, laptop, smart phone, tablet computer and portable wearable set
It is standby.
Optionally, if being somebody's turn to do the iris image Enhancement Method application based on histogram in systems, which may include clothes
Business end and client.Fig. 1 shows the application scenario diagram of iris image Enhancement Method application in systems based on histogram.Its
In, it is attached between server-side and client by network, client acquisition or obtains iris image, server-side is from client
End obtains iris image, and client specifically can be video camera, camera, scanner or other equipment for having camera function
(mobile phone or tablet computer etc.), or it is stored with the storage equipment of iris image.Client can be one, or plural number
It is a.Server-side can specifically be realized with a server or be realized with the server cluster that a plurality of servers form.
In one embodiment, as shown in Fig. 2, providing a kind of iris image Enhancement Method based on histogram, in this way
It is illustrated, includes the following steps for applying in computer equipment：
S10：Iris image collection is obtained, iris image collection includes iris image, and iris image includes user identifier.
Wherein, iris image collection refers to the image collection being made of iris image, and iris image refers to and set by camera shooting
The obtained image of iris of standby shooting user's inside of eye.Optionally, iris image collection can be acquires in real time, can also be with
It is stored in advance in computer equipment.One iris image collection may include the iris image of a user, also may include more
The iris image of a user.For example, an iris image concentrates the iris image including N number of user, if each user has M width
Iris image, then the iris image collection just has M*N width iris image.Preferably, it includes at least two width rainbows that iris image, which is concentrated,
Film image.User identifier refers to the mark of iris image owning user, for classifying to iris image according to owning user,
The corresponding user identifier of each iris image, the iris image of same user correspond to identical user identifier.
In a specific embodiment, the iris image that predetermined quantity can be obtained by shooting the eyes of user forms rainbow
Film image collection, or the pre-stored iris image of acquisition predetermined quantity forms iris image collection from computer equipment, or
Person passes through the eyes fetching portion iris image of shooting user, then the pre-stored rainbow of another part is obtained from computer equipment
Film image, the two collectively constitute iris image collection.
Preferably, it may be selected in same time period, acquire several iris images of several users as iris image collection.
For example, can be acquired at the noon of rainy days, it can also be acquired in the afternoon of fine day, can be avoided the iris image of acquisition in this way
Different iris images is concentrated to cause contrast to differ larger problem because of light variation.
S20：The contrast for the iris image that iris image is concentrated is calculated, and according to the descending sequence of contrast to rainbow
Film image concentrates the corresponding iris image of each user identifier to be ranked up, and obtains the corresponding initial iris sequence of each user identifier
Column.
Wherein, contrast is a kind of index for measuring picture quality, and specifically, the contrast of iris image is image black
With white ratio, for characterizing gradual change level of the iris image from black to white.The ratio is bigger, illustrates iris image from black to white
Gradual change level it is more, so that color representation is abundanter.Influence of the contrast to visual effect is very crucial, in general compares
Degree is bigger, and the image the clear eye-catching, and the color also the distinct gorgeous.The high iris image of contrast is thin in some dark portion scenes
It is more obvious that section performance, clarity and high-speed moving object show upper advantage.
Initial iris sequence refers to that the corresponding iris image of each user identifier is arranged according to the descending sequence of contrast
Arrange the iris sequence of composition.The corresponding iris image of same user identifier is ordered from large to small composition according to contrast
Iris sequence is the corresponding sub- iris sequence of the user identifier.Specifically, one by one to several iris images of each user identifier
Degree of comparing calculates, and sequence to each user identifier corresponding several iris images descending according to contrast carry out
Sequence, obtains the corresponding sub- iris sequence of each user identifier.The bigger iris image of contrast, clarity also can be higher, because
Iris image is concentrated the corresponding iris image of each user identifier to arrange according to the sequence of contrast from big to small by this.Such as：
There is N number of user identifier in initial iris sequence, each user identifier includes M width iris image, then there is N number of sub- iris sequence,
And this N number of sub- iris sequence together constitutes initial iris sequence, the iris image in every sub- iris sequence is according to comparison
What degree was ordered from large to small.
It is readily appreciated that ground, since contrast is to measure a kind of important indicator of picture quality, can be compared by calculating
The contrast of every width iris image, and it is based on same user identifier, according to the descending sequence of contrast to iris image collection
In the iris image standard that is ranked up, and then the biggish iris image of contrast is chosen as iris image, after being convenient for
It is continuous therefrom to select the biggish iris image of contrast and handled, obtain the iris image of more textural characteristics.
S30：The sequence descending according to contrast obtains pre- from the corresponding initial iris sequence of each user identifier
If the iris image of quantity, initial iris collection is formed.
Wherein, preset quantity is a pre-set numerical value, subsequent again for choosing a certain number of iris images
Carry out enhancing processing.Optionally, which can set according to the requirement of training sample amount.Such as：If subsequent
In model training, it is desirable that the training samples number of each user identifier is P, then can set preset quantity as P.Optionally, may be used
The value of preset quantity to be arranged according to the quantity of the corresponding iris image of each user identifier.For example, in each user identifier
In the case that the image of acquisition is 30 width, corresponding preset quantity can be set to 10 width, i.e., only needs in this 30 width iris figure
As in, according to the size order of contrast, according to from greatly to small selection in the corresponding initial iris sequence of each user identifier
10 width iris images are as initial iris collection.Initial iris collection is that the contrast numerical value chosen from initial iris sequence leans on
The set of the iris image composition of preceding preset quantity.Initial iris collection is formed by choosing the biggish iris image of contrast,
To exclude the lesser iris image of contrast, reduce some redundant images, mitigates the work of subsequent iris image enhancing processing
It measures, accelerates the speed of iris image enhancing processing, improve the treatment effeciency of subsequent iris image.Simultaneously as choosing comparison
Spending biggish iris image can be improved the enhancing degree of iris image as initial iris collection, and then promote iris image
Discrimination.
S40：The initial iris image carry out office that the initial iris is concentrated using adaptive histogram equalization algorithm
Portion's enhancing processing, obtains the first enhancing iris image collection.
Wherein, adaptive histogram equalization (Adaptive Histogram Equalization, AHE) algorithm uses
Mobile child windows technology carries out histogram equalization to the child window region comprising initial iris image pixel, that is, finds out the area
Lowest gray value and highest gray value in domain, equalize initial iris image histogram in the corresponding region of the child window,
Accordingly and by the grey scale mapping principle of the initial iris image histogram equalization of whole picture, to be processed in the corresponding region of child window
Image pixel assignment again.Be readily appreciated that ground, initial iris image gray value is integrally relatively low, histogram distribution gray value compared with
Small region, therefore comparatively concentrated in low gray level areas, after histogram equalization, increase its intensity profile model
It encloses, and the distance between each gray level is also increased, in entire gray level more uniformly, effectively extends initial iris
The intensity profile range of image improves pair of initial iris image so that initial iris image brightness increases to a certain extent
Degree of ratio.
Local enhancement refers to the treatment process enhanced the local message of image, in a specific embodiment, leads to
It crosses and the initial iris image of whole picture is divided into multiple sub-blocks, be distributed to all of initial iris image using algorithm of histogram equalization
Sub-block region, the superposition calculated by sub-block region-based histogram equalization adaptively enhance the local detail letter of iris image
Breath.Therefore, after carrying out local enhancement to initial iris image using adaptive histogram equalization algorithm, so that initial iris figure
As retaining image detail information as much as possible, local grain details also can be adjusted adaptively, and the inside for enhancing image is thin
Section, the detailed information of whole picture iris image is relatively sharp, so as to obtain texture-rich clearly the first enhancing iris image
Collection, can be improved subsequent accuracy of identification.
In the present embodiment, the gray value for the initial iris image that initial iris is concentrated is that adaptive histogram equalization is calculated
The gray value of the input of method, the first enhancing iris image is the output of adaptive histogram equalization algorithm.By using movement
Child windows technology carries out histogram equalization to initial iris image, has adjusted the dynamic range of iris image gray value, pass through
Adaptive histogram equalization is carried out to the part of iris image, has preferably highlighted local feature, while effectively extension is initial
The dynamic range of iris image grey scale pixel value has simultaneously refined interior details, so that the grain details of iris image become apparent.
S50：The first enhancing iris image that first enhancing iris image is concentrated is sharpened using Laplace operator
Processing, obtains the second enhancing iris image collection.
Wherein, the first enhancing iris image refers to the initial iris image concentrated to initial iris using self-adapting histogram
Equalization algorithm carries out the iris image obtained after enhancing processing.Laplace operator (Laplacian operator) is a kind of
Second Order Differential Operator, suitable for improving because image caused by the diffusing reflection of light is fuzzy.Its principle is to record image in camera shooting
During, light diffusing reflection to its peripheral region, this diffusing reflection due to light are caused a degree of mould of image by luminous point
Paste, fog-level it is opposite with for the image shot under normal conditions, often constant times of Laplace operator, therefore,
Image can be reduced to image progress Laplace operator sharpening transformation to obscure, and improve the clarity of image.Therefore, by right
First enhancing iris image is sharpened processing, and the edge details feature of prominent first enhancing iris image improves the first increasing
The contour sharpness of strong iris image.
Edge contrast refers to the transformation being sharpened to image, for reinforcing object boundary and image detail in image.
Second enhancing iris image refers to that the iris image concentrated to the first enhancing iris is sharpened processing using Laplace operator
The iris image obtained afterwards.First enhancing iris image is after Laplace operator Edge contrast, image edge detailss feature
The clarity at the clear zone edge of the first enhancing iris image is also improved while being reinforced, to protect the first enhancing iris
The details of image.
Optionally, the first enhancing iris image can be using the process that Laplace operator is sharpened：It is general with drawing
Laplacian operater seeks second dervative to the gray value of the first enhancing iris image pixel, and second dervative is equal at zero corresponding pixel just
It is the edge pixel of image, what iris texture edge can be more clear by such processing shows, to obtain texture
The richer clearly iris training set of details improves recognition effect.
Further, during carrying out enhancing processing to initial iris using adaptive histogram equalization algorithm,
Mode by then passing through mobile child window carries out histogram equalization to initial iris image, can introduce making an uproar for amplification thus
Sound generates interference.Therefore, it is filtered, can be inhibited by self-adapting histogram using the Laplace operator in Edge contrast
Equalization algorithm carries out the noise introduced during local enhancement, so that the second enhancing iris detailed information more horn of plenty.This reality
It applies in example, first acquisition iris image collection, the iris image degree of comparing that iris image is concentrated is calculated, and extract iris
The biggish iris image of contrast forms initial iris collection in image set, to reduce the bad iris image of quality, reduces
Redundant operation is conducive to the efficiency of the enhancing degree for improving iris image and subsequent enhancing processing.Then to initial iris collection
In initial iris image using adaptive histogram equalization algorithm carry out local enhancement processing, have adjusted initial iris image
The dynamic range of gray value has preferably highlighted local feature, while having refined interior details, finally increases to enhanced first
Strong iris image is sharpened processing, to inhibit to carry out what local enhancement introduced in the process by adaptive histogram equalization algorithm
Noise, while the second enhancing iris image is obtained after Edge contrast, the details of more iris images is remained, is improved on the whole
The contrast of iris image, is more clear the textural characteristics of iris image, to obtain richer clear of grain details
Iris training set, improve the accuracy rate of subsequent identification.
In one embodiment, as shown in figure 3, in step S10, that is, iris image collection is obtained, is specifically comprised the following steps：
S11：The measured distance for obtaining human eye and camera in real time, if measured distance is sent out not within the scope of distance threshold
Send prompting message.
Wherein, measured distance refers to the distance of the eye distance camera of user, and distance threshold refers to the mistake of measuring
Cheng Zhong, by testing a given pre-determined distance value repeatedly, if subject, at distance threshold, computer equipment is acquired
Image to compare the picture quality acquired at other positions more excellent.Distance threshold range refers to set above and below distance threshold
Boundary, it is readily appreciated that ground in a certain range that measured distance fluctuates above and below distance threshold, can also take and clearly scheme
Picture.Under the conditions of guaranteeing picture quality clearly, image is quickly shot for convenience, can be set the distance threshold ± a%'s
Numberical range is as distance threshold range, and optionally, a can be 5,10 or 15 etc..Prompt information is for prompting user to carry out
So as to shooting clear image, prompt information includes but is not limited to arrow logo (arrows of such as different directions), text for corresponding adjustment
Word prompt information (such as hypertelorism, distance appropriate or hypotelorism) and voice messaging is (such as " woulding you please close camera ", "
Acquisition " or " woulding you please far from camera ") etc..
After getting measured distance, measured distance is judged whether within the scope of distance threshold, if not in distance threshold model
In enclosing, prompt information is sent, user is adjusted correspondingly according to prompt information, then obtains measured distance, until measured distance
Until within the scope of distance threshold, through guidance user within the scope of distance threshold, be conducive to the iris figure for improving subsequent acquisition
The quality of picture.
It in a specific embodiment, can be using the focal length of infrared camera as distance by taking infrared camera as an example
Threshold value can specifically be adjusted, according to the clarity of image in such a way that infrared camera itself is manually or automatically focused
Determine the focal length of the camera.
In the present embodiment, corresponding prompt information is sent by the comparison to measured distance and distance threshold range, it can
To guide user rapidly to adjust position, the efficiency of iris image acquiring is improved.
S12：If measured distance within the scope of distance threshold, controls camera and is continuously shot, iris image is obtained
Collection.
It is to be appreciated that being shot in this case when distance of the eyes of user apart from camera is within the scope of distance threshold
The iris better quality of acquisition.Multiple iris images of an available same people are continuously shot, it is convenient and efficient, it is subsequent
Enhancing processing provides the iris image collection of better quality.
In the present embodiment, by obtaining the measured distance of eyes of user and camera, and by measured distance and distance threshold
Range is compared, and feeds back corresponding prompt information to user according to comparison result, and user is adjusted according to prompt information, when
In threshold range, control camera is continuously shot measured distance, is obtained iris image, be can be convenient and quickly get
Iris image also improves the quality of iris image.
In one embodiment, as shown in figure 4, in step S20, i.e. the comparison of the iris image of calculating iris image concentration
Degree, specifically comprises the following steps：
S21：The gray value that iris image concentrates each pixel of iris image is obtained, and successively using each pixel as in
Imago element.
Wherein, pixel (Pixel) is the basic element of digital picture, and pixel is in analog image digitlization to continuous sky
Between carry out discretization and obtain.Each pixel has integer row (height) and integer arranges (width) position coordinates, while each pixel
With integer gray value or color value.Piece image is made of many pixels.Specifically, digital image data can use square
Battle array indicates, therefore digital picture can be analyzed and be handled using matrix theory and matrix algorithm.The picture of gray level image
Prime information is exactly a matrix, the height of the row correspondence image of matrix, the width of matrix column correspondence image, matrix element correspondence image
Pixel, the value of matrix element is exactly the gray value of pixel, it indicate gray level image in color depth.Specifically, can pass through
Image information acquisition tool gets the corresponding gray value of each pixel of iris image.The corresponding path of image is provided, is led to
It crosses path and reads image under the path.For example, can be realized by imread function：
I=imread (' D:\lena.jpg')；
Wherein, jpg is the format of image, and lean is the title of image, " D:" be lean image path, I be lean scheme
As corresponding matrix.Center pixel refers in given region, the pixel positioned at center.It, successively will be every in this implementation
Pixel refers in given region centered on a pixel, by pixel centered on each pixel in region.For example, area
Have 15 pixels in domain, this 15 pixels successively centered on pixel, then just there is 15 center pixels.When the pixel on boundary is made
When for center pixel, boundary pixel can be regarded as center pixel by way of extending pixel, i.e., not deposited in boundary pixel neighborhood
Pixel gray value be arranged to it is equal with the boundary pixel gray value.Such as one the matrix of iris image be：
Wherein, the gray value of the pixel of the first row first row is 22, and pixel is not present in left part and top, then counting
When calculating contrast, the gray value of its left part and the pixel on top is arranged to the gray value of size identical with the boundary pixel,
That is the gray value of left part and top is 22.
S22：According to default neighborhood size, calculate the gray value of each center pixel and the gray value of corresponding neighborhood territory pixel it
Difference.
Wherein, neighborhood territory pixel refers to the pixel adjacent with center pixel position, for example, the pixel p positioned at coordinate (x, y) has
Two levels and two vertical adjacent pixels, one away from (x, y) unit distance of each pixel.Coordinate is respectively：(x-1,y),
(x+1,y),(x,y-1),(x,y+1).This pixel set is defined as 4 neighborhoods of pixel p, is indicated with N4 (p).In addition, pixel p
There are also 4 diagonal adjacent pixels, coordinate is：(x-1,y-1),(x+1,y-1),(x-1,y+1),(x+1,y+1).This four diagonal
Adjacent pixel and N4 (p) are collectively referenced as 8 neighborhoods of pixel P, are indicated with N8 (P).
If default neighborhood size takes 4, that is, take 4 neighborhoods, then each center pixel and the gray value of the pixel of corresponding neighborhood it
Difference has 4, if the gray value of center pixel is indicated with h (x, y), then the difference of the gray value of the pixel of itself and corresponding 4 neighborhood can
It is obtained by following formula：
q1=h (x-1, y)-h (x, y)；
q2=h (x, y-1)-h (x, y)；
q3=h (x+1, y)-h (x, y)；
q4=h (x, y+1)-h (x, y)；
It is readily appreciated that ground, when center pixel is boundary pixel, the difference q of corresponding gray value1、q2、q3、q4In at least
Having a value is 0.
S23：Line number and columns based on default neighborhood size He the iris image homography, obtain in the iris image
The number of the difference of gray value.
For example, set the corresponding matrix of an iris image asThen matrix M
Line number m=3, columns n=5.It is readily appreciated that ground, by image information acquisition tool, it is corresponding that the iris image can be got
Matrix, and then obtain the line number and columns of matrix.
If default neighborhood size is 4, the line number and columns of matrix are respectively m and n, then the number k of the difference of gray value can lead to
Following formula is crossed to obtain：
K=4 × (m-2) × (n-2)+3 × (2 × (m-2)+2 × (n-2))+4 × 2；
If default neighborhood size is 8, the line number and columns of matrix are respectively m and n, then the number k of the difference of gray value can lead to
Following formula is crossed to obtain：
K=8 × (m-2) × (n-2)+6 × (2 × (m-2)+2 × (n-2))+4 × 3.
S24:The difference of the gray value of center pixel each in the iris image and the gray value of corresponding neighborhood territory pixel is carried out
Square summation after divided by the difference of gray value in the iris image number, obtain the contrast of the iris image.
Wherein, the contrast of iris image is indicated with C, and the difference of gray value is respectively q1、q2…qk, k is positive integer.Iris
The specific formula for calculation of the contrast C of image is as follows：
C=(q1 2+q2+…+qk 2)/；
By formula it is found that contrast C is a specific numerical value.
In the present embodiment, the gray value of each pixel of iris image is obtained first, and successively using each pixel as in
Imago element, according to default neighborhood size, calculates the gray value of center pixel and the gray value difference of default neighborhood pixel, the gray scale
After the number of value difference value is calculated by the size of default neighborhood and the line number and columns of iris image homography, by the rainbow
Divided by ash after the gray value of each center pixel carries out square summation with the gray value difference of corresponding neighborhood territory pixel in film image
The number of angle value difference, acquired result are the contrast of the iris image.It can be simple by step S21 to step S24
Rapidly calculate the contrast of iris image, moreover it is possible to by comparing the high iris image of contrast screening mass.
In one embodiment, in step S40, the initial iris is concentrated using adaptive histogram equalization algorithm
Initial iris image carries out local enhancement processing, obtains the first enhancing iris image collection, specifically includes：
Default subgraph block is obtained, and according to the sequence of positions of default subgraph block to corresponding block of pixels in initial iris image
Carry out histogram equalization processing；
Wherein, histogram equalization processing is carried out to block of pixels corresponding in initial iris image, specifically included：
Obtain the number of each gray value in the histogram of block of pixels；
Number based on each gray value calculates the cumulative distribution function of each gray value；
Cumulative distribution function based on each gray value carries out greyscale transform process to block of pixels, the picture after being equalized
Plain block.
Wherein, it presets subgraph block and refers to pre-set mobile child window, for as to block of pixels degree of comparing
The standard of adjustment.It is to be appreciated that default subgraph block is smaller, it includes information content it is fewer, the contrast stretching journey of block of pixels
It spends bigger.For example, the size of default subgraph block A is 32 × 32, the size for presetting subgraph block B is 8 × 8, then presets B pairs of subgraph block
The level of stretch of the contrast for the block of pixels answered is greater than the level of stretch of the contrast of the default corresponding block of pixels of subgraph block A.Picture
Plain block refers to the subgraph block that initial iris image divide acquisition.Such as initial iris image size is 64 × 64, by it
Divide equally according to 2 × 2, then there are 4 block of pixels, the size of each block of pixels is 32 × 32.According to the sequence of positions of default subgraph block
Refer to the sequence of each block of pixels position according to subgraph block, sequence such as first from top to bottom again from left to right, Huo Zhexian
Sequence again from top to bottom from left to right.For example, an initial iris image is divided equally according to M × N, according to the position of default subgraph block
Sequence can be：The sequence of the first row, the second row ... M row, is also possible to the sequence of first row, secondary series ... Nth column.
Specifically, it is moved in the block of pixels of initial iris image with default subgraph block, and presses the sequence of positions of block of pixels
It is traversed, histogram equalization is carried out to block of pixels, block of pixels is grasped by the sequence of positions according to default subgraph block
Make, the local message of iris image is adaptively adjusted, and the interior details of initial iris image are increased.
The histogram of image is the statistical relationship for describing each gray value frequency of occurrences in image, and reflection is in piece image
The number that each gray value occurs.The cumulative distribution function for calculating each gray value refers to the number for getting each gray value
Afterwards, the distribution function number for being less than or equal to each gray value obtained after cumulative, for example, N (n1)、N(n2)…N(nk)
It is n to be less than or equal to gray value in histogramkNumber, then gray value be rkCorresponding cumulative distribution function is：N(rk)=N
(n1)+N(n2)+…N(nk).Greyscale transform process specific method is：Using the cumulative distribution function being calculated as transformation letter
Number carries out greyscale transformation by cumulative distribution function to each block of pixels in initial iris image, so that gray value is opposite
The region more concentrated has transformed to biggish region, improves the contrast of the block of pixels in initial iris image.
In a specific embodiment, the histogram of block of pixels can be obtained by image information tool, then statistical pixel
The number of each gray value of the corresponding histogram of block；Calculate the cumulative distribution function of each gray value；Based on cumulative distribution letter
Several pairs of block of pixels carry out greyscale transform process, the block of pixels after being equalized.Greyscale transformation is carried out by accumulation transforming function transformation function,
The histogram distribution of the block of pixels of initial iris image is changed to and is uniformly distributed histogram distribution, by using cumulative function pair
Gray value is adjusted the effect for realizing the contrast enhancing of initial iris image.It is to be appreciated that passing through these three steps
Realize the histogram equalization of the respective pixel block in initial iris image.
In the present embodiment, by default subgraph block in the block of pixels of initial iris image according to the sequence of positions of subgraph block into
Histogram equalization processing is being carried out after row traversal, so that the dynamic range of the grey scale pixel value of initial iris image obtains effectively
Extension, and local message is also adaptively adjusted, and interior details are enhanced.
In one embodiment, as shown in figure 5, in step S50, i.e., enhance rainbow to the first enhancing iris image is concentrated first
Film image is sharpened processing using Laplace operator, specifically comprises the following steps：
S51：The gray value for obtaining each pixel for the first enhancing iris image that the first enhancing iris image is concentrated, uses
Laplace operator is sharpened the gray value of each pixel, the grey scale pixel value after being sharpened.
Specifically, the first enhancing iris image that can directly read in the first enhancing iris image concentration, obtains each rainbow
Film image grey scale pixel value, specific read in mode is similar with step S21, and details are not described herein.
Laplace operator based on second-order differential is defined as：
For the first enhancing iris image R (x, y), second dervative is：
Therefore, Laplace operatorFor:
Obtain Laplace operatorLater, Laplace operator is usedTo the gray value of the first enhancing iris image
Each grey scale pixel value of R (x, y) is all sharpened according to following formula, the grey scale pixel value after being sharpened, in formula, g (x,
It y) is the grey scale pixel value after sharpening.
S52：Based on the grey scale pixel value after sharpening in the first enhancing iris image, corresponding second enhancing iris figure is obtained
Picture.
The gray value that grey scale pixel value after sharpening is replaced at former (x, y) pixel is obtained into the second enhancing iris image.
In a specific embodiment, Laplace operatorFour neighborhoods are selected to sharpen pattern matrix
The one first enhancing iris image that pattern matrix H concentrates the first enhancing iris image, which is sharpened, using four neighborhoods carries out La Pula
This operator sharpens.
As shown in Fig. 6 (a) and Fig. 6 (b), illustrates and self-adapting histogram is carried out to the initial iris image of a width (Fig. 6 (a))
Iris image i.e. second after equalization algorithm enhancing and Laplace operator sharpening enhances the comparison of iris image (Fig. 6 (b))
Figure.As can be seen that the overall contrast of initial iris image is lower, the second enhancing iris image relative to initial iris image,
The dynamic range of gray value is effectively adjusted, and the local message that do not know in 6 (a), local detail information are preferably presented
It highlights (iris image in eye image visually becomes clear), edge details are relatively abundanter.
In the present embodiment, each pixel for the first enhancing iris image that the first enhancing iris image is concentrated is obtained first
Gray value, laplacian spectral radius processing is carried out to it, obtained again after the grey scale pixel value after being sharpened it is corresponding second increase
Strong iris image.Iris image after adaptive histogram equalization algorithm enhancing processing is used into Laplace operator
It is sharpened, what image edge detailss feature introduced during inhibiting the first enhancing iris image to enhance while being reinforced makes an uproar
Sound, to protect the details of the first enhancing iris image.In addition, above-mentioned steps are not only simple and convenient, improve at iris image
The real-time of reason, and obtain the second enhancing iris image edge details feature after handling and more protrude clear, iris image collection
Overall contrast obtain larger raising, enhance the textural characteristics of iris image, be conducive to the identification for improving iris image
Accuracy rate.
It is worth noting that in order to verify the validity of the iris image Enhancement Method based on histogram, according to this reality
It applies the method for step S11 and step S12 in example and acquires 50 human eye iris images, each human eye 6 opens total 600 width iris image
Collection calculates the contrast of iris image collection, chooses 3 forward width of each human eye contrast, wherein 2 width are used as training, 1 width is used as
Verifying.By this 300 iris images after the adaptive histogram equalization algorithm in the present embodiment carries out local enhancement, and
The iris image of enhancing is sharpened processing using the method for step S51 to step S52 in the present embodiment, obtains that treated
Training set and verifying collection.Texture feature extraction is distinguished by unprocessed training set and by processing training set, and recognizer passes through
It calculates Euclidean distance or is realized by support vector machines (Support Vector Machine, SVM) classifier, calculating ratio
Reinforcing effect compared with discrimination, as the iris image enhancing algorithm based on histogram.As the result is shown：Untreated iris
The discrimination of image is 83%, and treated through the iris image Enhancement Method based on histogram in the present embodiment for iris image
Discrimination is 99.3%, and discrimination improves 16.3%.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
In one embodiment, a kind of iris image enhancement device based on histogram is provided, it should the iris based on histogram
Iris image Enhancement Method in image intensifier device and above-described embodiment based on histogram corresponds.As shown in fig. 7, the base
It include that iris image collection obtains module 10, iris retrieval module 20, initial rainbow in the iris image enhancement device of histogram
Film collection, which obtains module 30, first, enhances iris image collection acquisition module 40 and the second enhancing iris image collection acquisition module 50.Its
In, iris image collection obtains module 10, iris retrieval module 20, initial iris collection and obtains the enhancing iris of module 30, first
Image set obtains module 40 and the second enhancing iris image collection obtains in the realization function and above-described embodiment of module 50 based on straight
The corresponding step of the iris image Enhancement Method of square figure corresponds, and to avoid repeating, the present embodiment is not described in detail one by one.
Iris image collection obtains module 10, and for obtaining iris image collection, iris image collection includes iris image, iris figure
As including user identifier.
Iris retrieval module 20, the contrast of the iris image for calculating iris image concentration, and according to comparison
It spends descending sequence and concentrates the corresponding iris image of each user identifier to be ranked up iris image, obtain each user
Identify corresponding initial iris sequence.
Initial iris collection obtains module 30, for the foundation contrast from each user identifier corresponding initial iris sequence
Descending sequence obtains the iris image of preset quantity, forms initial iris collection.
First enhancing iris image collection obtains module 40, for using adaptive histogram equalization algorithm to initial iris
The initial iris image concentrated carries out local enhancement processing, obtains the first enhancing iris image collection.
Second enhancing iris image collection obtains module 50, the first enhancing iris for concentrating to the first enhancing iris image
Image is sharpened processing using Laplace operator, obtains the second enhancing iris image collection.
Specifically, it includes measured distance detection unit 11, iris image collection acquiring unit that iris image collection, which obtains module 10,
12。
Measured distance detection unit 11, for obtaining the measured distance of human eye and camera in real time, if measured distance does not exist
Within the scope of distance threshold, then prompting message is sent.
Iris image collection acquiring unit 12, if controlling camera progress for measured distance within the scope of distance threshold
It is continuously shot, obtains iris image collection.
Specifically, iris retrieval module 20 further includes contrast computing unit 21, is concentrated for calculating iris image
Iris image contrast.
Specifically, contrast computing unit 21 includes that gray value obtains subelement 211, the difference of gray value obtains subelement
212, the difference number of gray value obtains subelement 213 and contrast computation subunit 214.
Gray value obtains subelement 211, the gray value for concentrating each pixel of iris image for obtaining iris image, and
Successively by pixel centered on each pixel.
The difference of gray value obtains subelement 212, for calculating the gray scale of each center pixel according to default neighborhood size
The difference of the gray value of value and corresponding neighborhood territory pixel.
The difference number of gray value obtains subelement 213, for corresponding to square with the iris image based on default neighborhood size
The line number and columns of battle array, obtain the number of the difference of gray value in the iris image.
Contrast computation subunit 214, for by the gray value of center pixel each in the iris image and corresponding neighborhood
Divided by the number of the difference of gray value in the iris image after the difference progress square summation of the gray value of pixel, the iris figure is obtained
The contrast of picture.
Specifically, the first enhancing iris image collection obtains module 40 for obtaining default subgraph block, and according to default subgraph
The sequence of positions of block carries out histogram equalization processing to block of pixels corresponding in initial iris image；
Wherein, histogram equalization processing is carried out to block of pixels corresponding in initial iris image, specifically included：
Obtain the number of each gray value in the histogram of block of pixels；
Number based on each gray value calculates the cumulative distribution function of each gray value；
Cumulative distribution function based on each gray value carries out greyscale transform process to block of pixels, the picture after being equalized
Plain block.
Specifically, it includes gray value acquiring unit 51 and the second increasing after sharpening that the second enhancing iris image collection, which obtains module 50,
Strong iris image acquisition unit 52.
Gray value acquiring unit 51 after sharpening, the first enhancing iris image concentrated for obtaining the first enhancing iris image
Each pixel gray value, be sharpened using gray value of the Laplace operator to each pixel, after being sharpened
Grey scale pixel value.
Second enhancing iris image acquisition unit 52, for based on the pixel grey scale after being sharpened in the first enhancing iris image
Value obtains corresponding second enhancing iris image.
Specific restriction about the iris image enhancement device based on histogram may refer to above for based on histogram
The restriction of the iris image Enhancement Method of figure, details are not described herein.In the above-mentioned iris image enhancement device based on histogram
Modules can be realized fully or partially through software, hardware and combinations thereof.Above-mentioned each module can be embedded in the form of hardware
Or independently of in the processor in computer equipment, can also be stored in a software form in the memory in computer equipment,
The corresponding operation of the above modules is executed in order to which processor calls.
In one embodiment, a kind of computer equipment is provided, which can be client, internal junction
Composition can be as shown in Figure 8.The computer equipment includes processor, memory and the network interface connected by system bus.
Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory of the computer equipment includes non-easy
The property lost storage medium and built-in storage.The non-volatile memory medium is stored with operating system and computer program.The interior storage
Device provides environment for the operation of operating system and computer program in non-volatile memory medium.The network of the computer equipment
Interface is used to communicate with external terminal by network connection.To realize that one kind is based on when the computer program is executed by processor
The iris image Enhancement Method of histogram.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor realize that above-described embodiment is based on histogram when executing computer program
Iris image Enhancement Method the step of, such as step S10 shown in Fig. 2 to step S50.Alternatively, processor executes computer
The function of each module/unit of iris image enhancement device of the above-described embodiment based on histogram, such as Fig. 7 institute are realized when program
The module 10 shown is to module 50.To avoid repeating, which is not described herein again.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program realizes the step of iris image Enhancement Method of the above-described embodiment based on histogram when being executed by processor, alternatively, meter
Calculation machine program realizes each module/unit of iris image enhancement device of the above-described embodiment based on histogram when being executed by processor
Function, to avoid repeating, which is not described herein again.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided by the present invention,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that：It still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of iris image Enhancement Method based on histogram, which is characterized in that including：
Iris image collection is obtained, the iris image collection includes iris image, and the iris image includes user identifier；
The contrast for the iris image that the iris image is concentrated is calculated, and according to the descending sequence of contrast to the rainbow
Film image concentrates the corresponding iris image of each user identifier to be ranked up, and obtains the corresponding initial iris sequence of each user identifier
Column；
The sequence descending according to contrast obtains present count from the corresponding initial iris sequence of each user identifier
The iris image of amount forms initial iris collection；
It is carried out at local enhancement using the initial iris image that adaptive histogram equalization algorithm concentrates the initial iris
Reason, obtains the first enhancing iris image collection；
The the first enhancing iris image concentrated to the first enhancing iris image is sharpened processing using Laplace operator,
Obtain the second enhancing iris image collection.
2. the iris image Enhancement Method based on histogram as described in claim 1, which is characterized in that the acquisition iris figure
Image set, including：
The measured distance of human eye and camera is obtained in real time, if the measured distance, not within the scope of distance threshold, transmission mentions
Show message；
If the measured distance within the scope of distance threshold, controls the camera and is continuously shot, the iris is obtained
Image set.
3. the iris image Enhancement Method based on histogram as described in claim 1, which is characterized in that described to calculate the rainbow
The contrast for the iris image that film image is concentrated, including：
The gray value that the iris image concentrates each pixel of iris image is obtained, and successively by picture centered on each pixel
Element；
According to default neighborhood size, the difference of the gray value of each center pixel and the gray value of corresponding neighborhood territory pixel is calculated；
Line number and columns based on the default neighborhood size He the iris image homography, obtain described in the iris image
The number of the difference of gray value；
The difference of the gray value of center pixel each in the iris image and the gray value of corresponding neighborhood territory pixel is subjected to a square summation
Later divided by the number of the difference of gray value described in the iris image, the contrast of the iris image is obtained.
4. the iris image Enhancement Method based on histogram as described in claim 1, which is characterized in that described using adaptive
The initial iris image that algorithm of histogram equalization concentrates the initial iris carries out local enhancement processing, including：
Default subgraph block is obtained, and according to the sequence of positions of the default subgraph block to corresponding block of pixels in initial iris image
Carry out histogram equalization processing；
Wherein, histogram equalization processing is carried out to block of pixels corresponding in initial iris image, including：
Obtain the number of each gray value in the histogram of the block of pixels；
Number based on each gray value calculates the cumulative distribution function of each gray value；
Cumulative distribution function based on each gray value carries out greyscale transform process to block of pixels, the pixel after being equalized
Block.
5. the iris image Enhancement Method based on histogram as described in claim 1, which is characterized in that described to described first
The first enhancing iris image that enhancing iris image is concentrated is sharpened processing using Laplace operator, including：
The gray value of each pixel for the first enhancing iris image that the first enhancing iris image is concentrated is obtained, it is general using drawing
Laplacian operater is sharpened the gray value of each pixel, the grey scale pixel value after being sharpened；
Based on the grey scale pixel value after sharpening described in the first enhancing iris image, corresponding second enhancing iris image is obtained.
6. a kind of iris image enhancement device based on histogram, which is characterized in that including：
Iris image collection obtains module, and for obtaining iris image collection, the iris image collection includes iris image, the iris
Image includes user identifier；
Iris retrieval module, for calculating the contrast for the iris image that the iris image is concentrated, and according to contrast
Descending sequence concentrates the corresponding iris image of each user identifier to be ranked up iris image, obtains each user's mark
Know corresponding initial iris sequence；
Initial iris collection obtains module, for from the corresponding initial iris sequence of each user identifier according to contrast by greatly to
Small sequence obtains the iris image of preset quantity, forms initial iris collection；
First enhancing iris image collection obtains module, for using adaptive histogram equalization algorithm to the initial iris collection
In initial iris image carry out local enhancement processing, obtain the first enhancing iris image collection；
Second enhancing iris image collection obtains module, the first enhancing iris figure for concentrating to the first enhancing iris image
As being sharpened processing using Laplace operator, the second enhancing iris image collection is obtained.
7. the iris image enhancement device based on histogram as claimed in claim 6, which is characterized in that the first enhancing rainbow
Film image collection obtains module, is also used to obtain default subgraph block, and according to the sequence of positions of the subgraph block to initial iris figure
Corresponding block of pixels carries out histogram equalization processing as in；Wherein, block of pixels corresponding in initial iris image is carried out straight
Square figure equalization processing, including：
Obtain the number of each gray value in the histogram of the block of pixels；
Number based on each gray value calculates the cumulative distribution function of each gray value；
Cumulative distribution function based on each gray value carries out greyscale transform process to block of pixels, the pixel after being equalized
Block.
8. the iris image enhancement device based on histogram as claimed in claim 6, which is characterized in that the second enhancing rainbow
Film image collection obtains module, including：
Gray value acquiring unit after sharpening enhances iris image for obtaining the first enhancing iris image is concentrated first
The gray value of each pixel is sharpened, the picture after being sharpened using gray value of the Laplace operator to each pixel
Plain gray value；
Second enhancing iris image acquisition unit, for based on the pixel grey scale after being sharpened described in the first enhancing iris image
Value obtains corresponding second enhancing iris image.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of iris image Enhancement Method described in 5 any one based on histogram.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In iris figure of the realization as described in any one of claim 1 to 5 based on histogram when the computer program is executed by processor
The step of image intensifying method.
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