CN106248070A - A kind of navigator started based on iris identification - Google Patents
A kind of navigator started based on iris identification Download PDFInfo
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- CN106248070A CN106248070A CN201610548382.0A CN201610548382A CN106248070A CN 106248070 A CN106248070 A CN 106248070A CN 201610548382 A CN201610548382 A CN 201610548382A CN 106248070 A CN106248070 A CN 106248070A
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- 238000000034 method Methods 0.000 claims abstract description 83
- 238000005070 sampling Methods 0.000 claims abstract description 15
- 238000003708 edge detection Methods 0.000 claims description 35
- 238000005520 cutting process Methods 0.000 claims description 22
- 210000001747 pupil Anatomy 0.000 claims description 14
- 238000012937 correction Methods 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 238000010606 normalization Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 7
- 238000004904 shortening Methods 0.000 claims description 7
- 238000005728 strengthening Methods 0.000 claims description 7
- 230000001629 suppression Effects 0.000 claims description 7
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- 239000013013 elastic material Substances 0.000 description 6
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- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- 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
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Abstract
A kind of navigator started based on iris identification of the present invention, including navigator and the iris identification device that is connected with the navigator signal of telecommunication, described iris identification device includes: (1) sampling module;(2) pretreatment module;(3) feature coding module, for the feature of iris image is extracted and encoded, it includes that LBP operator processes submodule, for the second time LBP operator for the first time and processes submodule, for the third time LBP operator process submodule and the 4th LBP operator process submodule;(4) codes match module.Invention increases the relatedness of central point and other neighborhood of surrounding, disclosure satisfy that the image texture of different scale and frequency, after repeatedly LBP operator processes submodule process, under not affecting the central point relatedness with surrounding neighbors, constantly reduce code length, saved memory space, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtain higher robustness.
Description
Technical field
The present invention relates to navigator system design field, be specifically related to a kind of navigator started based on iris identification.
Background technology
In correlation technique, the navigator with identification verification function generally uses basic LBP (local binary patterns) operator
Iris image feature is extracted and encoded, and LBP operator is a kind of to describe the method for textural characteristics in the range of gradation of image, right
For illumination variation, there is the strongest robustness, thus be widely used in the texture feature extraction of image.
Basic LBP operator is commonly defined as: by central point n in 3 × 3 windowsc8 neighborhood n about0,...n7Group
Becoming, defined in it, texture T is: T=(n0-nc,n1-nc,...,n7-nc), it is carried out binary conversion treatment, with ncFor threshold value, neighbour
8 points in territory and ncRelatively, if being labeled as 1 more than the value of central point, 0 otherwise it is labeled as.Texture T after binaryzation is: T=
(sgn(n0-nc),sgn(n1-nc),...,sgn(n7-nc)), whereinThrough calculating, will obtain with ncFor
8 binary numbers at center, then are weighted different pixels position suing for peace just obtaining the LBP value of central point, wherein LBP value
Computing formula be:Pixel each in image is carried out LBP computing, just can obtain
LBP texture description to image.
But, owing to basic LBP operator cover only 8 neighborhood territory pixels of central point so that it is with other neighborhood of surrounding
Relatedness is the most comprehensive, it is impossible to meet the image texture of different scale and frequency.
Summary of the invention
For the problems referred to above, the present invention provides the one that a kind of recognition speed is fast, identification range is wide to open based on iris identification
Dynamic navigator, solves the navigator using basic LBP operator that iris image feature is extracted and encoded in correlation technique
The problem that system can not process the image texture of different scale and frequency.
The purpose of the present invention realizes by the following technical solutions:
A kind of navigator started based on iris identification, including navigator and the iris identification that is connected with the navigator signal of telecommunication
Device, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, internal four of described navigator set casing
Corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining, correcting iris image and gather the information of iris image, due to reality acquisition
In approximately the same plane, understand slightly deviation between iris image and the iris image of standard acquisition, need the iris that reality is obtained
Image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
(2) pretreatment module, for positioning the iris image obtained and normalized, it includes that light speckle is filled out
Filling submodule, described smooth speckle is filled submodule and is used for being filled with each hot spot point detected in iris image, fills
The gray value of four the envelope points up and down in the non-spot area that Shi Liyong is adjacent with light speckle calculates the ash of light speckle
Angle value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith the K in 5 × 5 windows
Pixel is compared to calculate LBP value, and described K pixel is with a ncCentered by be distributed in a ncPeriphery, if ncCoordinate be
(xc,yc), the computing formula of LBP value is:
Wherein, described K pixel is labeled as n0~nK, the span of K is [20,24], 1st-LBP (xc,yc) take
Value scope is [0, K];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module also includes:
(1) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(2) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(3) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The invention have the benefit that
1, image rectification submodule is set, and defines updating formula, improve the precision of image procossing;
2, light speckle is set and fills submodule, and define the gray value computing formula of light speckle, remain rainbow well
The structural information of film image, the iris image after filling can position effectively;
3, the first positioning unit arranged, its Canny edge detection operator passing through improvement and Hough loop truss are to iris
Inside and outside circle positions, it is simple to the speed positioning and improve iris of iris;
4, the first time LBP operator arranged processes submodule, adds the relatedness of central point and other neighborhood of surrounding, energy
Enough meet the image texture of different scale and frequency;
5, the second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP calculation
Son processes submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduces code length, has saved storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtain higher robustness.
Accompanying drawing explanation
The invention will be further described to utilize accompanying drawing, but the embodiment in accompanying drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain according to the following drawings
Other accompanying drawing.
Fig. 1 is the iris identification device connection diagram of the present invention.
Fig. 2 is the navigator schematic diagram of the present invention.
Detailed description of the invention
The invention will be further described with the following Examples.
Embodiment 1
Seeing Fig. 1, Fig. 2, a kind of navigator started based on iris identification of the present embodiment, including navigator and and navigator
The iris identification device that the signal of telecommunication connects, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, described navigator set casing internal four
Individual corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining iris image and gathering the information of iris image;
(2) pretreatment module, for obtaining, correcting iris image and gather the information of iris image, owing to reality obtains
Iris image and the iris image of standard acquisition between in approximately the same plane can slightly deviation, need the rainbow that reality is obtained
Film image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith 20 in 5 × 5 windows
Individual pixel is compared to calculate LBP value, and described 20 pixels are with a ncCentered by be distributed in a ncPeriphery, if ncSeat
It is designated as (xc,yc), the computing formula of LBP value is:
Wherein, described 20 pixels are labeled as n0~n20, 1st-LBP (xc,yc) span be [0,20];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module includes:
(1) light speckle fills submodule: for being filled with each hot spot point detected in iris image, during filling
The gray value utilizing four the envelope points up and down in the non-spot area adjacent with light speckle calculates the gray scale of light speckle
Value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
(2) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(3) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(4) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The present embodiment arranges light speckle and fills submodule, remains the structural information of iris image well, after filling
Iris image can position effectively;Arrange first positioning unit, its by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, it is simple to the speed positioning and improve iris of iris;The first time arranged
LBP operator processes submodule, adds the relatedness of central point and other neighborhood of surrounding, it is possible to meet different scale and frequency
Image texture;The second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP operator
Process submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduce code length, save storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtained higher robustness, use CASIA
When V1.0 iris storehouse is tested, result is as follows:
Embodiment 2
Seeing Fig. 1, Fig. 2, a kind of navigator started based on iris identification of the present embodiment, including navigator and and navigator
The iris identification device that the signal of telecommunication connects, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, internal four of described navigator set casing
Corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining iris image and gathering the information of iris image;
(2) pretreatment module, for obtaining, correcting iris image and gather the information of iris image, owing to reality obtains
Iris image and the iris image of standard acquisition between in approximately the same plane can slightly deviation, need the rainbow that reality is obtained
Film image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith 21 in 5 × 5 windows
Individual pixel is compared to calculate LBP value, and described 21 pixels are with a ncCentered by be distributed in a ncPeriphery, if ncSeat
It is designated as (xc,yc), the computing formula of LBP value is:
Wherein, described 21 pixels are labeled as n0~n21, 1st-LBP (xc,yc) span be [0,21];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module includes:
(1) light speckle fills submodule: for being filled with each hot spot point detected in iris image, during filling
The gray value utilizing four the envelope points up and down in the non-spot area adjacent with light speckle calculates the gray scale of light speckle
Value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
(2) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(3) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(4) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The present embodiment arranges light speckle and fills submodule, remains the structural information of iris image well, after filling
Iris image can position effectively;Arrange first positioning unit, its by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, it is simple to the speed positioning and improve iris of iris;The first time arranged
LBP operator processes submodule, adds the relatedness of central point and other neighborhood of surrounding, it is possible to meet different scale and frequency
Image texture;The second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP operator
Process submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduce code length, save storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtained higher robustness, use CASIA
When V1.0 iris storehouse is tested, result is as follows:
Embodiment 3
Seeing Fig. 1, Fig. 2, a kind of navigator started based on iris identification of the present embodiment, including navigator and and navigator
The iris identification device that the signal of telecommunication connects, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, internal four of described navigator set casing
Corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining, correcting iris image and gather the information of iris image, due to reality acquisition
In approximately the same plane, understand slightly deviation between iris image and the iris image of standard acquisition, need the iris that reality is obtained
Image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
(2) pretreatment module, for positioning and normalized the iris image obtained;
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith 22 in 5 × 5 windows
Individual pixel is compared to calculate LBP value, and described 22 pixels are with a ncCentered by be distributed in a ncPeriphery, if ncSeat
It is designated as (xc,yc), the computing formula of LBP value is:
Wherein, described 22 pixels are labeled as n0~n21, 1st-LBP (xc,yc) span be [0,22];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module includes:
(1) light speckle fills submodule: for being filled with each hot spot point detected in iris image, during filling
The gray value utilizing four the envelope points up and down in the non-spot area adjacent with light speckle calculates the gray scale of light speckle
Value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
(2) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(3) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(4) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The present embodiment arranges light speckle and fills submodule, remains the structural information of iris image well, after filling
Iris image can position effectively;Arrange first positioning unit, its by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, it is simple to the speed positioning and improve iris of iris;First arranged
Secondary LBP operator processes submodule, adds the relatedness of central point and other neighborhood of surrounding, it is possible to meet different scale and frequency
Image texture;The second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP calculation
Son processes submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduces code length, has saved storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtained higher robustness, use CASIA
When V1.0 iris storehouse is tested, result is as follows:
Embodiment 4
Seeing Fig. 1, Fig. 2, a kind of navigator started based on iris identification of the present embodiment, including navigator and and navigator
The iris identification device that the signal of telecommunication connects, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, internal four of described navigator set casing
Corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining, correcting iris image and gather the information of iris image, due to reality acquisition
In approximately the same plane, understand slightly deviation between iris image and the iris image of standard acquisition, need the iris that reality is obtained
Image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
(2) pretreatment module, for positioning and normalized the iris image obtained;
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith 23 in 5 × 5 windows
Individual pixel is compared to calculate LBP value, and described 23 pixels are with a ncCentered by be distributed in a ncPeriphery, if ncSeat
It is designated as (xc,yc), the computing formula of LBP value is:
Wherein, described 23 pixels are labeled as n0~n21, 1st-LBP (xc,yc) span be [0,23];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module includes:
(1) light speckle fills submodule: for being filled with each hot spot point detected in iris image, during filling
The gray value utilizing four the envelope points up and down in the non-spot area adjacent with light speckle calculates the gray scale of light speckle
Value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
(2) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(3) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(4) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The present embodiment arranges light speckle and fills submodule, remains the structural information of iris image well, after filling
Iris image can position effectively;Arrange first positioning unit, its by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, it is simple to the speed positioning and improve iris of iris;The first time arranged
LBP operator processes submodule, adds the relatedness of central point and other neighborhood of surrounding, it is possible to meet different scale and frequency
Image texture;The second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP operator
Process submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduce code length, save storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtained higher robustness, use CASIA
When V1.0 iris storehouse is tested, result is as follows:
Embodiment 5
Seeing Fig. 1, Fig. 2, a kind of navigator started based on iris identification of the present embodiment, including navigator and and navigator
The iris identification device that the signal of telecommunication connects, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing sets
Buffer layer, described buffer layer is had to be filled between navigator set casing, navigator housing, internal four of described navigator set casing
Corner is provided with grip block, is provided with the tensioning bullet being arranged in parallel between each grip block described and navigator set casing inwall
Spring, the vertical section in described navigator set casing both sides is provided with several louvres, and described louvre is that low inside and high outside shape is arranged.
Preferably, it is characterized in that, described buffer layer is that elastic material is made.
Preferably, it is characterized in that, described tensioning spring two ends connect for fixing.
Preferably, it is characterized in that, described iris identification device includes:
(1) sampling module, for obtaining, correcting iris image and gather the information of iris image, due to reality acquisition
In approximately the same plane, understand slightly deviation between iris image and the iris image of standard acquisition, need the iris that reality is obtained
Image carries out plane correction, sets image rectification submodule, and the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual
Standard deviation between the iris image and each pixel point value of the iris image of standard acquisition that obtain;
(2) pretreatment module, for positioning and normalized the iris image obtained;
Preferably, it is characterized in that, described iris identification device also includes:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith 24 in 5 × 5 windows
Individual pixel is compared to calculate LBP value, and described 24 pixels are with a ncCentered by be distributed in a ncPeriphery, if ncSeat
It is designated as (xc,yc), the computing formula of LBP value is:
Wherein, described 24 pixels are labeled as n0~n21, 1st-LBP (xc,yc) span be [0,24];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith week
Enclosing the relatedness of neighborhood, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3
× 3 windows, by the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point
ncCalculating, computing formula is:
C, for the third time LBP operator process submodule, process the square after submodule processes for shortening through second time LBP operator
The feature coding length of shape image, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|
=rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large
After take front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: on the basis of processing after submodule processes at third time LBP operator
Continuing to reduce code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and data base
Feature coding is compared, and completes the identification to identity.
Wherein, described pretreatment module includes:
(1) light speckle fills submodule: for being filled with each hot spot point detected in iris image, during filling
The gray value utilizing four the envelope points up and down in the non-spot area adjacent with light speckle calculates the gray scale of light speckle
Value, a light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,
y2)、P3(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
(2) coarse positioning submodule: fill submodule with light speckle and be connected, is used for carrying out iris image cutting and the most fixed
Position pupil position, during cutting centered by described pupil position, the iris image after filling hot spot cut by the radius of 5 times
Cut;
(3) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(4) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
Wherein, described fine positioning submodule includes the downsampling unit being sequentially connected with, first positioning unit and again positions
Unit, described downsampling unit is for carrying out down-sampling to the iris image after cutting, and described first positioning unit is used for passing through
Iris inside and outside circle is positioned by the Canny edge detection operator and the Hough loop truss that improve, and described positioning unit again is used for
It is accurately positioned on iris image with the parameter that first positioning unit positions.
Wherein, the Canny edge detection operator of described improvement is the suppression that vertical direction only carries out non-maximum
Canny edge detection operator.
Wherein, the Canny edge detection operator of described improvement is the Canny limit carrying out strong rim detection only with high threshold
Edge detective operators.
The present embodiment arranges light speckle and fills submodule, remains the structural information of iris image well, after filling
Iris image can position effectively;Arrange first positioning unit, its by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, it is simple to the speed positioning and improve iris of iris;The first time arranged
LBP operator processes submodule, adds the relatedness of central point and other neighborhood of surrounding, it is possible to meet different scale and frequency
Image texture;The second time LBP operator arranged processes submodule, for the third time LBP operator and processes submodule and the 4th LBP operator
Process submodule, under not affecting the central point relatedness with surrounding neighbors, constantly reduce code length, save storage sky
Between, decrease amount of calculation, improve recognition speed, enhance recognition accuracy, obtained higher robustness, use CASIA
When V1.0 iris storehouse is tested, result is as follows:
Last it should be noted that, above example is only in order to illustrate technical scheme, rather than the present invention is protected
Protecting the restriction of scope, although having made to explain to the present invention with reference to preferred embodiment, those of ordinary skill in the art should
Work as understanding, technical scheme can be modified or equivalent, without deviating from the reality of technical solution of the present invention
Matter and scope.
Claims (9)
1. the navigator started based on iris identification, including navigator and the iris identification that is connected with the navigator signal of telecommunication
Device, described navigator includes:
Set casing, navigator housing, it is characterised in that: described navigator set casing surface upper and lower with navigator housing is provided with and subtracts
Shake layer, described buffer layer is filled between navigator set casing, navigator housing, internal four turnings of described navigator set casing
Place is provided with grip block, is provided with the tensioning spring being arranged in parallel, institute between each grip block described and navigator set casing inwall
Stating the vertical section in navigator set casing both sides and be provided with several louvres, described louvre is that low inside and high outside shape is arranged.
A kind of navigator started based on iris identification the most according to claim 1, is characterized in that, described buffer layer is bullet
Property material is made.
A kind of navigator started based on iris identification the most according to claim 2, is characterized in that, described tensioning spring two
End connects for fixing.
A kind of navigator started based on iris identification the most according to claim 3, is characterized in that, described iris identification device
Including:
(1) sampling module, for obtaining, correcting iris image and gather the information of iris image, the iris obtained due to reality
In approximately the same plane, understand slightly deviation between image and the iris image of standard acquisition, need the iris image that reality is obtained
Carrying out plane correction, set image rectification submodule, the updating formula that described image rectification submodule uses is:
Wherein, and I (x, y)AThe iris image that expression reality obtains, and I (x, y)BRepresent the iris image of standard acquisition, actual acquisition
Iris image and standard acquisition iris image each pixel point value between standard deviation;
(2) pretreatment module, for positioning the iris image obtained and normalized, it includes that light speckle fills son
Module, described smooth speckle is filled submodule and is used for being filled with each hot spot point detected in iris image, sharp during filling
The gray value of light speckle is calculated with the gray value of four the envelope points up and down in the non-spot area adjacent with light speckle,
A light speckle in definition iris image is P0(x0,y0), described four envelope points are followed successively by P1(x1,y1)、P2(x2,y2)、P3
(x3,y3)、P4(x4,y4), the gray value computing formula of definition light speckle is:
A kind of navigator started based on iris identification the most according to claim 4, is characterized in that, described iris identification device
Also include:
(3) feature coding module, for the feature of iris image is extracted and is encoded, including:
A, for the first time LBP operator process submodule: for any point n in iris imagecWith K pixel in 5 × 5 windows
Point is compared to calculate LBP value, and described K pixel is with a ncCentered by be distributed in a ncPeriphery, if ncCoordinate be (xc,
yc), the computing formula of LBP value is:
Wherein, described K pixel is labeled as n0~nK, the span of K is [20,24], 1st-LBP (xc,yc) value model
Enclose for [0, K];
B, for the second time LBP operator process submodule, for strengthening described some n on the premise of ensureing code lengthcWith surrounding neighbors
Relatedness, it is with a nc8 neighborhood territory pixel points as sub-center point, be denoted as nvc0,nvc1,...,nvc7, use 3 × 3 windows,
By the average of entire pixels in windowReplace the value of sub-center point, re-use LBP operator to central point ncCarry out
Calculating, computing formula is:
C, for the third time LBP operator process submodule, process the iris figure after submodule processes for shortening through second time LBP operator
The feature coding length of picture, it is with a ncCentered by, according to self-defining function { n in the window of 3 × 3vcj,|nvcj-nc|=
rank4(|nvci-nc|, i=0,1 ..., 7), j=0,1,2,3} selects 4 sub-center points to calculate, and computing formula is:
Wherein, rank4(|nvci-nc|, i=0,1 ..., 7) represent 7 | nvci-nc| value arrange from small to large after take
Front 4 numbers, nvcjRepresent 4 the sub-center points chosen;
D, the 4th LBP operator process submodule: continue on the basis of processing after submodule processes at third time LBP operator
Reducing code length, computing formula is:
After having calculated, output represents the coding of iris image feature;
(4) codes match module, for receiving the coding of described expression iris image feature and by itself and the feature in data base
Coding is compared, and completes the identification to identity.
A kind of navigator started based on iris identification the most according to claim 5, is characterized in that, described pretreatment module
Also include:
(1) coarse positioning submodule: fill submodule with light speckle and be connected, for carrying out cutting Primary Location pupil to iris image
Hole site, during cutting centered by described pupil position, the iris image after filling hot spot cuts by the radius of 5 times;
(2) fine positioning submodule: be connected with coarse positioning submodule, is used for being accurately positioned iris region;
(3) normalization submodule, for being launched into the iris image of fixed resolution by the iris region behind location.
A kind of navigator started based on iris identification the most according to claim 6, is characterized in that, described fine positioning submodule
Block includes the downsampling unit being sequentially connected with, first positioning unit and positioning unit again, and described downsampling unit is for cutting
Iris image after cutting carries out down-sampling, described first positioning unit for by improve Canny edge detection operator and
Iris inside and outside circle is positioned by Hough loop truss, and described positioning unit again is for the parameter positioned with first positioning unit
Iris image is accurately positioned.
A kind of navigator started based on iris identification the most according to claim 7, is characterized in that, described improvement
Canny edge detection operator is the Canny edge detection operator of the suppression that vertical direction only carries out non-maximum.
A kind of navigator started based on iris identification the most according to claim 8, is characterized in that, described improvement
Canny edge detection operator is the Canny edge detection operator carrying out strong rim detection only with high threshold.
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