CN106204958B - A kind of ATM machine input unit being identified by iris - Google Patents
A kind of ATM machine input unit being identified by iris Download PDFInfo
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- CN106204958B CN106204958B CN201610548331.8A CN201610548331A CN106204958B CN 106204958 B CN106204958 B CN 106204958B CN 201610548331 A CN201610548331 A CN 201610548331A CN 106204958 B CN106204958 B CN 106204958B
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Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
- G07F19/20—Automatic teller machines [ATMs]
- G07F19/201—Accessories of ATMs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/197—Matching; Classification
Abstract
A kind of ATM machine input unit being identified by iris of the present invention, including ATM machine input unit and the iris recognition device that is connect with ATM machine input unit electric signal, the iris recognition device include：(1) sampling module；(2) preprocessing module；(3) feature coding module, it extracts and encodes for the feature to iris image comprising first time LBP operator handles submodule, second of LBP operators processing submodule, third time LBP operators processing submodule and the 4th LBP operator and handles submodule；(4) codes match module.Invention increases the relevances of central point and the other neighborhoods of surrounding, it disclosure satisfy that different scale and the image texture of frequency, after the processing submodule processing of multiple LBP operators, in the case where not influencing the relevance of central point and surrounding neighbors, code length is constantly reduced, memory space has been saved, reduce calculation amount, recognition speed is improved, recognition accuracy is enhanced, has obtained higher robustness.
Description
Technical field
The present invention relates to ATM machine input unit design fields, and in particular to a kind of ATM machine being identified by iris is defeated
Enter device.
Background technology
In the related technology, ATM machine input unit generally use basic LBP (the local binary moulds being identified by iris
Formula) operator extracts and encodes to iris image feature, and LBP operators are textural characteristics within the scope of a kind of description gradation of image
Method has very strong robustness for illumination variation, to be widely used in the texture feature extraction of image.
Basic LBP operators are commonly defined as：By central point n in 3 × 3 windowscAnd 8 neighborhood n around it0,...n7Group
At, defined in texture T be：T=(n0-nc,n1-nc,...,n7-nc), binary conversion treatment is carried out to it, with ncFor threshold value, neighborhood
8 points and ncCompare, is labeled as 1 if more than the value of central point, is otherwise labeled as 0.Texture T after binaryzation is：T=(sgn
(n0-nc),sgn(n1-nc),...,sgn(n7-nc)), whereinBy calculating, will obtain with ncCentered on
8 binary numbers, summation then is weighted to different pixels position and just obtains the LBP values of central point, the wherein meter of LBP values
Calculating formula is：LBP operations are carried out to each pixel in image, figure can be obtained
The LBP texture descriptions of picture.
However, since basic LBP operators cover only 8 neighborhood territory pixels of central point, make itself and other neighborhoods around
Relevance is not comprehensive enough, cannot be satisfied different scale and the image texture of frequency.
Invention content
One kind that a kind of recognition speed is fast in view of the above-mentioned problems, the present invention provides, identification range is wide is known by iris
Other ATM machine input unit solves to use basic LBP operators to extract and encode iris image feature in the related technology
ATM machine input unit system cannot handle the problem of image texture of different scale and frequency.
The purpose of the present invention is realized using following technical scheme：
A kind of ATM machine input unit being identified by iris, including ATM machine input unit and with ATM machine input fill
The iris recognition device of electric signal connection is set, the ATM machine input unit includes：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining, correcting iris image and acquire the information of iris image, due to what is actually obtained
Can slightly have deviation between iris image and the iris image of standard acquisition in the same plane, need the iris to actually obtaining
Image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
(2) preprocessing module carries out positioning and normalized comprising hot spot point is filled out for the iris image to acquisition
Submodule is filled, the hot spot point filling submodule is filled for being filled to each hot spot point detected in iris image
The gray values of four envelope points up and down in non-spot area adjacent with hot spot point Shi Liyong calculates the ash of hot spot point
Angle value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith K in 5 × 5 windows
Pixel is compared to calculate LBP values, and the K pixel is with point ncCentered on be distributed in point ncPeriphery, if ncCoordinate be
(xc,yc), the calculation formula of LBP values is：
Wherein, the K pixel is labeled as n0~nK, the value range of K is [20,24], 1st-LBP (xc,yc) take
Value is ranging from [0, K]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module further includes：
(1) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(2) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(3) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
Beneficial effects of the present invention are：
1, image rectification submodule is set, and define updating formula, improves the precision of image procossing；
2, setting hot spot point fills submodule, and defines the gray value calculation formula of hot spot point, remains rainbow well
Positioning can be effectively performed in the structural information of film image, the iris image after filling；
3, the first positioning unit being arranged, by improved Canny edge detection operators and Hough loop truss to iris
Inside and outside circle is positioned, convenient for the speed of iris positioned and improve iris；
4, the first time LBP operator being arranged handles submodule, increases the relevance of central point and the other neighborhoods of surrounding, energy
Enough meet different scale and the image texture of frequency；
5, second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP being arranged are calculated
Subprocessing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, obtains higher robustness.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the iris recognition device connection diagram of the present invention.
Specific implementation mode
The invention will be further described with the following Examples.
Embodiment 1
Referring to Fig. 1, a kind of ATM machine input unit being identified by iris of the present embodiment, including ATM machine input unit
The iris recognition device being connect with ATM machine input unit electric signal, the ATM machine input unit include：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining iris image and acquiring the information of iris image；
(2) preprocessing module, for obtaining, correcting iris image and acquire the information of iris image, due to practical acquisition
Iris image and the iris image of standard acquisition between can slightly have deviation in the same plane, need the rainbow to actually obtaining
Film image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith 20 in 5 × 5 windows
A pixel is compared to calculate LBP values, and 20 pixels are with point ncCentered on be distributed in point ncPeriphery, if ncSeat
It is designated as (xc,yc), the calculation formula of LBP values is：
Wherein, 20 pixels are labeled as n0~n20, 1st-LBP (xc,yc) value range be [0,20]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module includes：
(1) hot spot point fills submodule：For being filled to each hot spot point detected in iris image, when filling
The gray scale of hot spot point is calculated using the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point
Value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(2) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(3) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(4) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
The present embodiment is arranged hot spot point and fills submodule, the structural information of iris image is remained well, after filling
Positioning can be effectively performed in iris image；The first positioning unit being arranged, by improved Canny edge detection operators and
Hough loop truss positions iris inside and outside circle, convenient for the speed of iris positioned and improve iris；The first time of setting
LBP operators handle submodule, increase the relevance of central point and the other neighborhoods of surrounding, disclosure satisfy that different scale and frequency
Image texture；Second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP operator being arranged
Processing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, has obtained higher robustness, used CASIA
It is as a result as follows when V1.0 irises library is tested：
Embodiment 2
Referring to Fig. 1, a kind of ATM machine input unit being identified by iris of the present embodiment, including ATM machine input unit
The iris recognition device being connect with ATM machine input unit electric signal, the ATM machine input unit include：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining iris image and acquiring the information of iris image；
(2) preprocessing module, for obtaining, correcting iris image and acquire the information of iris image, due to practical acquisition
Iris image and the iris image of standard acquisition between can slightly have deviation in the same plane, need the rainbow to actually obtaining
Film image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith 21 in 5 × 5 windows
A pixel is compared to calculate LBP values, and 21 pixels are with point ncCentered on be distributed in point ncPeriphery, if ncSeat
It is designated as (xc,yc), the calculation formula of LBP values is：
Wherein, 21 pixels are labeled as n0~n21, 1st-LBP (xc,yc) value range be [0,21]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module includes：
(1) hot spot point fills submodule：For being filled to each hot spot point detected in iris image, when filling
The gray scale of hot spot point is calculated using the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point
Value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(2) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(3) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(4) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
The present embodiment is arranged hot spot point and fills submodule, the structural information of iris image is remained well, after filling
Positioning can be effectively performed in iris image；The first positioning unit being arranged, by improved Canny edge detection operators and
Hough loop truss positions iris inside and outside circle, convenient for the speed of iris positioned and improve iris；The first time of setting
LBP operators handle submodule, increase the relevance of central point and the other neighborhoods of surrounding, disclosure satisfy that different scale and frequency
Image texture；Second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP operator being arranged
Processing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, has obtained higher robustness, used CASIA
It is as a result as follows when V1.0 irises library is tested：
Embodiment 3
Referring to Fig. 1, a kind of ATM machine input unit being identified by iris of the present embodiment, including ATM machine input unit
The iris recognition device being connect with ATM machine input unit electric signal, the ATM machine input unit include：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining, correcting iris image and acquire the information of iris image, due to what is actually obtained
Can slightly have deviation between iris image and the iris image of standard acquisition in the same plane, need the iris to actually obtaining
Image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
(2) preprocessing module carries out positioning and normalized for the iris image to acquisition；
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith 22 in 5 × 5 windows
A pixel is compared to calculate LBP values, and 22 pixels are with point ncCentered on be distributed in point ncPeriphery, if ncSeat
It is designated as (xc,yc), the calculation formula of LBP values is：
Wherein, 22 pixels are labeled as n0~n21, 1st-LBP (xc,yc) value range be [0,22]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module includes：
(1) hot spot point fills submodule：For being filled to each hot spot point detected in iris image, when filling
The gray scale of hot spot point is calculated using the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point
Value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(2) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(3) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(4) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
The present embodiment is arranged hot spot point and fills submodule, the structural information of iris image is remained well, after filling
Positioning can be effectively performed in iris image；The first positioning unit being arranged, by improved Canny edge detection operators and
Hough loop truss positions iris inside and outside circle, convenient for the speed of iris positioned and improve iris；The first time of setting
LBP operators handle submodule, increase the relevance of central point and the other neighborhoods of surrounding, disclosure satisfy that different scale and frequency
Image texture；Second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP operator being arranged
Processing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, has obtained higher robustness, used CASIA
It is as a result as follows when V1.0 irises library is tested：
Embodiment 4
Referring to Fig. 1, a kind of ATM machine input unit being identified by iris of the present embodiment, including ATM machine input unit
The iris recognition device being connect with ATM machine input unit electric signal, the ATM machine input unit include：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining, correcting iris image and acquire the information of iris image, due to what is actually obtained
Can slightly have deviation between iris image and the iris image of standard acquisition in the same plane, need the iris to actually obtaining
Image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
(2) preprocessing module carries out positioning and normalized for the iris image to acquisition；
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith 23 in 5 × 5 windows
A pixel is compared to calculate LBP values, and 23 pixels are with point ncCentered on be distributed in point ncPeriphery, if ncSeat
It is designated as (xc,yc), the calculation formula of LBP values is：
Wherein, 23 pixels are labeled as n0~n21, 1st-LBP (xc,yc) value range be [0,23]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module includes：
(1) hot spot point fills submodule：For being filled to each hot spot point detected in iris image, when filling
The gray scale of hot spot point is calculated using the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point
Value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(2) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(3) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(4) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
The present embodiment is arranged hot spot point and fills submodule, the structural information of iris image is remained well, after filling
Positioning can be effectively performed in iris image；The first positioning unit being arranged, by improved Canny edge detection operators and
Hough loop truss positions iris inside and outside circle, convenient for the speed of iris positioned and improve iris；The first time of setting
LBP operators handle submodule, increase the relevance of central point and the other neighborhoods of surrounding, disclosure satisfy that different scale and frequency
Image texture；Second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP operator being arranged
Processing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, has obtained higher robustness, used CASIA
It is as a result as follows when V1.0 irises library is tested：
Embodiment 5
Referring to Fig. 1, a kind of ATM machine input unit being identified by iris of the present embodiment, including ATM machine input unit
The iris recognition device being connect with ATM machine input unit electric signal, the ATM machine input unit include：
Outline border；
Touch control screen module includes a chip, in outline border described in the touch control screen Module-embedding；
Randomized blocks are defined as random array, the random number to randomly generate the set of number including 0-9 and period
Each of period and 0-9 in group number at least occur primary；
Processor is to handle data, and the processor is connected to the randomized blocks and the touch-control by conducting wire
The chip of formula screen module.
Preferably, characterized in that above-mentioned connection device has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Out, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
Preferably, characterized in that it is arranged in arrays that number and period in the random array are scattered in four rows.
Preferably, characterized in that the iris recognition device includes：
(1) sampling module, for obtaining, correcting iris image and acquire the information of iris image, due to what is actually obtained
Can slightly have deviation between iris image and the iris image of standard acquisition in the same plane, need the iris to actually obtaining
Image carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, it is practical
Standard deviation between the iris image of acquisition and each pixel point value of the iris image of standard acquisition；
(2) preprocessing module carries out positioning and normalized for the iris image to acquisition；
Preferably, characterized in that the iris recognition device further includes：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith 24 in 5 × 5 windows
A pixel is compared to calculate LBP values, and 24 pixels are with point ncCentered on be distributed in point ncPeriphery, if ncSeat
It is designated as (xc,yc), the calculation formula of LBP values is：
Wherein, 24 pixels are labeled as n0~n21, 1st-LBP (xc,yc) value range be [0,24]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith week
The relevance for enclosing neighborhood, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, with the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point
ncIt is calculated, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated square through second LBP operator for shortening
The feature coding length of shape image, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value arranged from small to large
After take preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For on the basis of treated for third time LBP operators processing submodule
Continue to reduce code length, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receive it is described indicate iris image feature coding and by its in database
Feature coding is compared, and completes the identification to identity.
Wherein, the preprocessing module includes：
(1) hot spot point fills submodule：For being filled to each hot spot point detected in iris image, when filling
The gray scale of hot spot point is calculated using the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point
Value, it is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(2) coarse positioning submodule：It is connect with hot spot point filling submodule, for iris image cut and tentatively fixed
Position pupil position, when cutting centered on the pupil position, 5 times of radius cuts the iris image after filling hot spot
It cuts；
(3) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(4) submodule is normalized, the iris image for the iris region after positioning to be launched into fixed resolution.
Wherein, the fine positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition
Unit, the downsampling unit are used to carry out down-sampling to the iris image after cutting, and the first positioning unit is for passing through
Improved Canny edge detection operators and Hough loop truss position iris inside and outside circle, and the reposition unit is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the improved Canny edge detection operators are the inhibition that non-maximum is only carried out to vertical direction
Canny edge detection operators.
Wherein, the improved Canny edge detection operators are the sides Canny that strong edge detection is carried out only with high threshold
Edge detective operators.
The present embodiment is arranged hot spot point and fills submodule, the structural information of iris image is remained well, after filling
Positioning can be effectively performed in iris image；The first positioning unit being arranged, by improved Canny edge detection operators and
Hough loop truss positions iris inside and outside circle, convenient for the speed of iris positioned and improve iris；The first time of setting
LBP operators handle submodule, increase the relevance of central point and the other neighborhoods of surrounding, disclosure satisfy that different scale and frequency
Image texture；Second of LBP operator processing submodule, third time LBP operators processing submodule and the 4th LBP operator being arranged
Processing submodule constantly reduces code length in the case where not influencing the relevance of central point and surrounding neighbors, and it is empty to have saved storage
Between, reduce calculation amount, improve recognition speed, enhance recognition accuracy, has obtained higher robustness, used CASIA
It is as a result as follows when V1.0 irises library is tested：
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although being explained in detail to the present invention with reference to preferred embodiment, those skilled in the art answer
Work as understanding, technical scheme of the present invention can be modified or replaced equivalently, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (7)
1. a kind of ATM machine input unit being identified by iris, characterized in that ATM machine input unit electric signal connects rainbow
Film identifier, the ATM machine input unit include：
Outline border；
Touch control screen module, the touch control screen module include a chip, outer described in the touch control screen Module-embedding
In frame；
Randomized blocks, the module immediately are defined as random array randomly generating the set of number including 0-9 and period,
Each of period and 0-9 in the random array number at least occur primary；
Processor, the processor to handle data, and the processor by conducting wire be connected to the randomized blocks and
The chip of the touch control screen module；
The iris recognition device includes：
(1) sampling module, for obtaining, correcting iris image and acquire the information of iris image, due to the iris actually obtained
Can slightly have deviation between image and the iris image of standard acquisition in the same plane, need the iris image to actually obtaining
Carry out plane correction, set image rectification submodule, the updating formula that described image correction module uses for：
Wherein, I (x, y)AIndicate the iris image actually obtained, I (x, y)BIndicate the iris image of standard acquisition, σbIndicate real
Standard deviation between each pixel point value of the iris image of iris image and standard acquisition that border obtains；
(2) preprocessing module carries out positioning and normalized for the iris image to acquisition comprising hot spot point filling
Module, hot spot point filling submodule is for being filled each hot spot point detected in iris image, profit when filling
The gray value of hot spot point is calculated with the gray value of four envelope points up and down in the non-spot area adjacent with hot spot point,
It is P to define a hot spot point in iris image0(x0,y0), four envelopes point is followed successively by P1(x1,y1)、P2(x2,y2)、P3
(x3,y3)、P4(x4,y4), the gray value calculation formula for defining hot spot point is：
(3) feature coding module is extracted and is encoded for the feature to iris image, including：
A, first time LBP operators handle submodule：For to any point n in iris imagecWith K pixel in 5 × 5 windows
Point is compared to calculate LBP values, and the K pixel is with point ncCentered on be distributed in point ncPeriphery, if ncCoordinate be (xc,
yc), the calculation formula of LBP values is：
Wherein, the K pixel is labeled as n0~nK, the value range of K is [20,24], 1st-LBP (xc,yc) value model
It encloses for [0, K]；
B, second of LBP operator handles submodule, for reinforcing the point n under the premise of ensureing code lengthcWith surrounding neighbors
Relevance, with point nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, using 3 × 3 windows,
With the mean value of entire pixels in windowInstead of the value of sub-center point, LBP operators are reused to central point ncIt carries out
It calculates, calculation formula is：
C, third time LBP operators handle submodule, and submodule is handled treated iris figure through second LBP operator for shortening
The feature coding length of picture, with point ncCentered on, according to custom function { n in 3 × 3 windowvcj,|nvcj-nc|=
rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3 } 4 sub-center points of selection are calculated, and calculation formula is：
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) indicate to 7 | nvci-nc| value carry out from small to large arrange after take
Preceding 4 numbers, nvcjIndicate the 4 sub-center points chosen；
D, the 4th LBP operator handles submodule：For continuing on the basis of treated in third time LBP operators processing submodule
Code length is reduced, calculation formula is：
Output indicates the coding of iris image feature after having been calculated；
(4) codes match module, for receiving the coding for indicating iris image feature and by itself and the feature in database
Coding is compared, and completes the identification to identity.
2. a kind of ATM machine input unit being identified by iris according to claim 1, characterized in that above-mentioned ATM
Machine input unit has：
A keyboard region is provided in the touch control screen module, the random array is shown in the keyboard region each time
Come, the position of this 10 symbols of period described in keyboard region and 0-9 generates at random.
3. a kind of ATM machine input unit being identified by iris according to claim 2, characterized in that it is described with
It is arranged in arrays that number and period in machine array are scattered in four rows.
4. a kind of ATM machine input unit being identified by iris according to claim 3, characterized in that described pre-
Processing module further includes：
(1) coarse positioning submodule：It is connect with hot spot point filling submodule, for cut simultaneously Primary Location pupil to iris image
Hole site, when cutting centered on the pupil position, 5 times of pupil radium cuts the iris image after filling hot spot
It cuts；
(2) fine positioning submodule：It is connect with coarse positioning submodule, for being accurately positioned iris region；
(3) submodule, the iris image for the iris region after being accurately positioned to be launched into fixed resolution are normalized.
5. a kind of ATM machine input unit being identified by iris according to claim 4, characterized in that the essence
Positioning submodule includes sequentially connected downsampling unit, first positioning unit and reposition unit, the downsampling unit
For carrying out down-sampling to the iris image after cutting, the first positioning unit is for passing through improved Canny edge detections
Operator and Hough loop truss position iris inside and outside circle, and the reposition unit is used to position with first positioning unit
Parameter be accurately positioned on iris image.
6. a kind of ATM machine input unit being identified by iris according to claim 5, characterized in that described to change
Into Canny edge detection operators be only vertical direction is carried out non-maximum inhibition a Canny edge detection operators.
7. a kind of ATM machine input unit being identified by iris according to claim 6, characterized in that described to change
Into Canny edge detection operators be only with high threshold carry out strong edge detection Canny edge detection operators.
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| CN107273834A (en) * | 2017-06-06 | 2017-10-20 | 宋友澂 | A kind of iris identification method and identifier |
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