CN102521576A - Iris location method - Google Patents
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention relates to an iris location method. The method comprises the following steps of: step 1, detecting spots in an iris image; step 2, judging whether the iris image shakes; step 3, initially locating a pupil; step 4, locating the iris. The method has the following benefits that: the iris is located by a two-dimensional round Gabor filter and a weighted calculus detection operator, interference on an iris identification system caused by noise information is reduced, internal and external boundaries can be quickly and accurately located in the iris image, and the stability and the accuracy of an iris location algorithm are improved.
Description
Technical field
The present invention relates to iris locating method, relate in particular to a kind of iris locating method based on two-dimensional circular Gabor wave filter and weighting infinitesimal analysis detection operator.
Background technology
Along with the development of infotech, the mankind have got into a unprecedented information age.Information security also becomes the hot issue that People more and more is paid close attention to.In daily life, we often need verify own perhaps other people identity, and reliable identity identification can make our life avoid trouble, and the safety of protection personal information, reliable identity recognition technology make that also finance and business transaction are more safe and effective.Traditional authentication is owing to very easily forging and losing; More and more be difficult to satisfy the demand of society; Development along with bio-science; The attention that living things feature recognition is safe with it, good reliability receives increasing people becomes the advanced subject of intersecting of subjects researchs such as applied mathematics and Flame Image Process and pattern-recognition.
Living things feature recognition combines with high-tech means such as biology sensor and biostatistics through computing machine, utilizes intrinsic physiological characteristic of human body and behavioural characteristic to discern the identity with a people of authentication.At present, common biometrics identification technology comprises mainly that fingerprint recognition, iris recognition, face are discerned mutually and speech recognition etc.The market of international iris recognition is keeping growth at a high speed always, expects 2015, can reach 1,481 hundred ten thousand dollars operation revenue.Iris recognition has bright development prospect, and be widely used in customs, field such as airport, bank, gate inhibition and information security.Along with reaching its maturity of iris recognition technology, will play the part of more and more important role aspect protection people's the information security.
Iris is the circular pigment barrier film around the eye pupil, and the abundant textured pattern of iris is the basis of iris authentication system, and iris recognition technology extracts exactly, analyzes and matees these textures.The uniqueness of iris texture makes iris become the fabulous human body biological characteristics that is used for identification with stability.Iris authentication system is at first gathered iris image; In the iris image that collects, cut apart iris region then; On iris image after the normalization, extract characteristic at last and mate,, determine whether to come from same individual through contrasting the similarity of two width of cloth iris images.Iris is to be in pupil (eyes black part) in addition, and sclera is with the annular tissue of interior (eyes white portion).Compare with other biological characteristic, iris has many remarkable advantages as the characteristic of identification, mainly comprises:
1. uniqueness is high: iris has highly unique with complicated textural characteristics, and iris texture has more than 100 degree of freedom, does not almost have the identical iris of textural characteristics;
2. good stability: iris is formed at embryonic period, embryonic phase, owing to receive the protection of cornea, it is less that iris receives the influence of external environment, and textural characteristics is stable;
3. antifalsification is good: the zoom feature that iris changes with light intensity and self be chatter clocklike, and the natural method of testing to false iris is provided, and the texture structure that changes iris almost is impossible;
4. noninvasive: obtaining of iris image do not need Body contact, in certain distance, just can obtain, and can not shine into uncomfortable human body.
Iris Location is the key link of iris authentication system, and the levels of precision of location is related to the feature extraction and the coupling of iris.So, Iris Location result's whether accurate accuracy and the high efficiency that directly has influence on iris authentication system.The eye image that iris image gathering system obtains comprises the parts such as eyelid, eyelashes, sclera, pupil of human eye, and Iris Location is exactly to detect the inner and outer boundary of iris, carries out separating process to other parts of iris and human eye.Iris has good ring texture, and by pupil to iris again to sclera, the stepped rising of the gray scale of image, this good marginal texture helps the location of iris and cuts apart.But eyelid and eyelashes may block iris region, and in concrete Iris Location process, suitable pre-service can be good at getting rid of and disturbs, and improves the stability and the accuracy of whole location algorithm.
In addition; In image acquisition process, the size of pupil can change along with the variation of photoenvironment, and eyelid and eyelashes block iris region; The distance of human eye and collecting device also is uncertain; And also exist certain angular relationship between them, even the therefore different images of same human eye, positioning result also exists otherness.In some classical iris authentication systems, utilize iris boundary to be similar to circular these characteristics, adopt the inner and outer boundary of non-concentrically ringed two circle model orientation irises.Because shape is known, can obtain corresponding circular parameter according to the border characteristics of iris.
Summary of the invention
The present invention proposes a kind of new iris locating method; Promptly detect the iris locating method of operator based on two-dimensional circular Gabor filtering and weighting infinitesimal analysis; Iris image is judged; Reduced the interference of noise information, improved the stability and the accuracy of Iris Location algorithm iris authentication system.
The objective of the invention is to realize through following technical scheme:
A kind of iris locating method may further comprise the steps:
Step 1, to the spot detection of iris image, specifically comprise step by step following:
Step 1.1, through camera head, the iris in the human eye is carried out IMAQ, utilize median filtering method that the iris image that obtains is carried out smoothing processing;
Step 1.2, the iris image after utilizing two-dimensional circular Gabor wave filter to smoothing processing carry out filter action, choose binary-state threshold then, adopt the method for binaryzation to confirm spot area;
Step 2, judge whether iris image rocks: to detected spot area in the step 1.2; Adopt least square method to calculate the determined ellipse in spot area border; If the ratio of oval length semiaxis is bigger, then iris image rocks, otherwise is iris image more clearly;
Step 3, pupil is carried out location just, specifically comprises step by step following:
Step 3.1, the iris image more clearly that obtains in the step 2 is contracted to original 0.2 times;
Step 3.2, utilize median filtering method that the iris image that dwindles in the step 3.1 is carried out smoothing processing;
Step 3.3, the maximal value of using two-dimensional circular Gabor wave filter to get filtered in the step 3.2 are carried out the first location of pupil, confirm the approximate location of pupil;
Step 4, iris is positioned, specifically comprises step by step following:
Step 4.1, utilize para-curve that the iris image that obtains in the step 3.2 is located upper and lower eyelid;
Step 4.2, the iris image that obtains in the step 3.2 carried out normalization, normalized Grad of iris image and normalized gray-scale value are subtracted each other, and the result that will subtract each other compares with 0.1, greater than 0.1 be the eyelashes zones, less than 0.1 be that non-eyelashes are regional;
Eyelash and eyelid in the iris image that obtains in step 4.3, the removal step 3.2;
Step 4.4, utilize weighting infinitesimal analysis operator that the inside and outside border of the iris image that obtains in the step 4.3 is positioned, accurately discerning inside and outside border is not circular iris image.
In the said step 1.2, the iris image after adopting two-dimensional circular Gabor wave filter to smoothing processing carries out convolution, and maximum point is the position of hot spot, and the maximal value of getting convolution results is M_max, thinks hot spot greater than the part of k*M_max.Said median filtering method is the 5*5 median filtering method.
Beneficial effect of the present invention is: adopt two-dimensional circular Gabor wave filter and weighting infinitesimal analysis to detect operator iris is positioned; Reduced the interference of noise information to iris authentication system; Can orient the inner and outer boundary in the iris image fast and accurately, improve the stability and the accuracy of Iris Location algorithm.
Description of drawings
According to accompanying drawing the present invention is done further explain below.
Fig. 1 is the process flow diagram of the described a kind of iris locating method of the embodiment of the invention;
Fig. 2 is the image that contains iris that collects;
Fig. 3 is the figure as a result that the iris image of two-dimensional circular Gabor wave filter after to smoothing processing carries out filter action;
Fig. 4 is spot area testing result figure;
Fig. 5 is the figure as a result after iris image dwindles smoothly;
Fig. 6 is eyelid positioning result figure;
Fig. 7 is eyelashes zone location figure as a result;
Fig. 8 is Iris Location figure as a result.
Embodiment
Describe content of the present invention for ease, at first some terms are defined.
Definition 1: iris.The center of eyeball is the pupil of black, and the outer intermarginal annular tissue of pupil is iris, and it demonstrates the textural characteristics of interlaced similar and spot, filament, striped, crypts.Same individual's iris can change the people's in life hardly, and the iris of different people is different fully.
Definition 2: binary-state threshold.The gray scale threshold value of being selected for use when image is carried out binaryzation.
Definition 3: binaryzation.Change into all values of entire image and have only two kinds of worth processes, generally these two kinds of values are 0 and 1 or 0 and 255.When the value on the image more than or equal to binary-state threshold the time, this puts to such an extent that the value two-value turns to 1 (or 255); When the value on the image less than binary-state threshold the time, this puts to such an extent that the value two-value turns to 0.
Definition 4: median filtering method.Median filtering method is a kind of Nonlinear Processing method that suppresses noise, for a given n numerical value a1, a2,, an } they are arranged according to size in order.When n was odd number, that numerical value that is positioned at the centre position was called the intermediate value of this n numerical value.When n was even number, the mean value that is positioned at two numerical value in centre position was called the intermediate value of this n numerical value.The output of certain pixel equals the intermediate value of each pixel grey scale in this pixel field behind the image medium filtering.
As shown in Figure 1, the described a kind of iris locating method of the embodiment of the invention may further comprise the steps:
Step 1, to the spot detection of iris image, specifically comprise step by step following:
Step 1.1, through camera head, the iris in the human eye is carried out IMAQ, the iris image that collects is as shown in Figure 2, utilizes median filtering method that the iris image that obtains is carried out smoothing processing;
Step 1.2, the iris image after utilizing two-dimensional circular Gabor wave filter to smoothing processing carry out filter action, and filtered is as shown in Figure 3, chooses binary-state threshold then, adopt the method for binaryzation to confirm spot area, and the light spot image that obtains is as shown in Figure 4;
Step 2, judge whether iris image rocks: to detected spot area in the step 1.2; Adopt least square method to calculate the determined ellipse in spot area border; If the ratio of oval length semiaxis is bigger, then iris image rocks, otherwise is iris image more clearly;
Step 3, pupil is carried out location just, specifically comprises step by step following:
Step 3.1, the iris image more clearly that obtains in the step 2 is contracted to original 0.2 times;
Step 3.2, utilize median filtering method that the iris image that dwindles in the step 3.1 is carried out smoothing processing, the iris image that obtains is as shown in Figure 5;
Step 3.3, the maximal value of using two-dimensional circular Gabor wave filter to get filtered in the step 3.2 are carried out the first location of pupil, confirm the approximate location of pupil;
Step 4, iris is positioned, specifically comprises step by step following:
Step 4.1, utilize para-curve that the iris image that obtains in the step 3.2 is located upper and lower eyelid, the eyelid positioning result is as shown in Figure 6;
Step 4.2, the iris image that obtains in the step 3.2 is carried out normalization; Normalized Grad of iris image and normalized gray-scale value are subtracted each other; And the result that will subtract each other compares with 0.1; Greater than 0.1 be eyelashes zones, less than 0.1 be that non-eyelashes are regional, the result is as shown in Figure 7 for the eyelashes zone location;
Eyelash and eyelid in the iris image that obtains in step 4.3, the removal step 3.2;
Step 4.4, utilize weighting infinitesimal analysis operator that the inside and outside border of the iris image that obtains in the step 4.3 is positioned, accurately discerning inside and outside border is not circular iris image, and Iris Location result is as shown in Figure 8.
Said step 1.2 is specially, and the iris image after adopting two-dimensional circular Gabor wave filter to smoothing processing carries out convolution, and maximum point is the position of hot spot, and the maximal value of getting convolution results is M_max, all thinks hot spot greater than the part of k*M_max.Said median filtering method is the 5*5 median filtering method.
The present invention is not limited to above-mentioned preferred forms; Anyone can draw other various forms of products under enlightenment of the present invention; No matter but on its shape or structure, do any variation; Every have identical with a application or akin technical scheme, all drops within protection scope of the present invention.
Claims (6)
1. the iris locating method based on two-dimensional circular Gabor wave filter and weighting infinitesimal analysis detection operator is characterized in that, may further comprise the steps:
Step 1: to the spot detection of iris image;
Step 2: judge whether iris image rocks;
Step 3: pupil is carried out location just; And
Step 4: iris is positioned.
2. iris locating method according to claim 1 is characterized in that, said step 1 further comprises:
Step 1.1): through camera head, the iris in the human eye is carried out IMAQ, utilize median filtering method that the iris image that obtains is carried out smoothing processing;
Step 1.2): the iris image after utilizing two-dimensional circular Gabor wave filter to smoothing processing carries out filter action, chooses binary-state threshold then, adopts the method for binaryzation to confirm spot area.
3. iris locating method according to claim 2; It is characterized in that, in said step 2, step 1.2) in detected spot area; Adopt least square method to calculate the determined ellipse in spot area border; If the ratio of oval length semiaxis is bigger, then iris image rocks, otherwise is iris image more clearly.
4. iris locating method according to claim 3 is characterized in that, said step 3 further comprises:
Step 3.1): the iris image more clearly that obtains in the step 2 is contracted to original 0.2 times;
Step 3.2): utilize median filtering method the iris image that dwindles) carries out smoothing processing to step 3.1;
Step 3.3): use two-dimensional circular Gabor wave filter to get step 3.2 maximal value of filtered is carried out the first location of pupil), confirms the approximate location of pupil.
5. iris locating method according to claim 4 is characterized in that, said step 4 further comprises:
Step 4.1): utilize para-curve the iris image that obtains) is located upper and lower eyelid to step 3.2;
Step 4.2): to step 3.2 iris image that obtains) carries out normalization; Normalized Grad of iris image and normalized gray-scale value are subtracted each other; And the result that will subtract each other compares with 0.1, greater than 0.1 be the eyelashes zones, less than 0.1 be that non-eyelashes are regional;
Step 4.3): remove step 3.2 eyelash and eyelid in the iris image that obtains);
The inside and outside border of the iris image that obtains step 4.4): utilize weighting infinitesimal analysis operator to step 4.3) positions, and accurately discerning inside and outside border is not circular iris image.
6. according to each described iris locating method of claim 2-5; It is characterized in that: said step 1.2); Iris image after adopting two-dimensional circular Gabor wave filter to smoothing processing carries out convolution; Maximum point is the position of hot spot, and the maximal value of getting convolution results is M_max, thinks hot spot greater than the part of k*M_max.
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| Application Number | Priority Date | Filing Date | Title |
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| CN2011104222341A CN102521576A (en) | 2011-12-16 | 2011-12-16 | Iris location method |
| CN2012104106684A CN102902970A (en) | 2011-12-16 | 2012-10-24 | Iris location method |
| PCT/CN2012/086665 WO2013087026A1 (en) | 2011-12-16 | 2012-12-14 | Locating method and locating device for iris |
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| CN2011104222341A CN102521576A (en) | 2011-12-16 | 2011-12-16 | Iris location method |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013087026A1 (en) * | 2011-12-16 | 2013-06-20 | 北京天诚盛业科技有限公司 | Locating method and locating device for iris |
| CN103198484A (en) * | 2013-04-07 | 2013-07-10 | 山东师范大学 | Iris image segmentation algorithm based on nonlinear dimension space |
| CN105631407A (en) * | 2015-12-18 | 2016-06-01 | 电子科技大学 | Forest musk deer iris positioning method |
| CN107871322A (en) * | 2016-09-27 | 2018-04-03 | 北京眼神科技有限公司 | Iris segmentation method and apparatus |
| CN110647787A (en) * | 2018-06-27 | 2020-01-03 | 厦门本能管家科技有限公司 | Private key generation and decryption method and system based on iris recognition |
| CN111144413A (en) * | 2019-12-30 | 2020-05-12 | 福建天晴数码有限公司 | Iris positioning method and computer readable storage medium |
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| CN104537342B (en) * | 2014-12-24 | 2017-08-11 | 福州大学 | A kind of express lane line detecting method of combination ridge border detection and Hough transformation |
| CN104850823B (en) * | 2015-03-26 | 2017-12-22 | 浪潮软件集团有限公司 | Quality evaluation method and device for iris image |
| CN105141938B (en) * | 2015-08-18 | 2017-12-01 | 深圳先进技术研究院 | Sight positioner |
| EP3337383B1 (en) * | 2015-08-21 | 2024-10-16 | Magic Leap, Inc. | Eyelid shape estimation |
| CN106326825B (en) * | 2015-08-26 | 2019-08-06 | 北京巴塔科技有限公司 | Iris edge localization method and iris authentication system |
| CN109657531A (en) * | 2018-09-18 | 2019-04-19 | 深圳先牛信息技术有限公司 | A kind of human face in-vivo detection method and detection device based on hot spot on eyeball |
| CN110084789B (en) * | 2019-04-15 | 2021-11-09 | 广西释码智能信息技术有限公司 | Quality evaluation method of iris image and computing equipment |
| CN110619272A (en) * | 2019-08-14 | 2019-12-27 | 中山市奥珀金属制品有限公司 | Iris image segmentation method |
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| CN113762077B (en) * | 2021-07-19 | 2024-02-02 | 沈阳工业大学 | Multi-biological feature iris template protection method based on double-grading mapping |
| CN114582008A (en) * | 2022-03-03 | 2022-06-03 | 北方工业大学 | Living iris detection method based on two wave bands |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1209073C (en) * | 2001-12-18 | 2005-07-06 | 中国科学院自动化研究所 | Identity discriminating method based on living body iris |
| GB2403864A (en) * | 2003-07-10 | 2005-01-12 | Ocuity Ltd | Pixel arrangement for an autostereoscopic display |
| US7756301B2 (en) * | 2005-01-26 | 2010-07-13 | Honeywell International Inc. | Iris recognition system and method |
| CN1298283C (en) * | 2003-11-18 | 2007-02-07 | 清华大学 | Iris image collecting method |
| CN101893858B (en) * | 2010-07-15 | 2012-01-25 | 华中科技大学 | Method for controlling distance between eyes of user and screen of electronic equipment |
| CN102521576A (en) * | 2011-12-16 | 2012-06-27 | 北京天诚盛业科技有限公司 | Iris location method |
-
2011
- 2011-12-16 CN CN2011104222341A patent/CN102521576A/en not_active Withdrawn
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2012
- 2012-10-24 CN CN2012104106684A patent/CN102902970A/en active Pending
- 2012-12-14 WO PCT/CN2012/086665 patent/WO2013087026A1/en active Application Filing
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013087026A1 (en) * | 2011-12-16 | 2013-06-20 | 北京天诚盛业科技有限公司 | Locating method and locating device for iris |
| CN103198484A (en) * | 2013-04-07 | 2013-07-10 | 山东师范大学 | Iris image segmentation algorithm based on nonlinear dimension space |
| CN103198484B (en) * | 2013-04-07 | 2015-11-18 | 山东师范大学 | Based on the iris segmentation algorithm of Nonlinear Scale Space Theory |
| CN105631407A (en) * | 2015-12-18 | 2016-06-01 | 电子科技大学 | Forest musk deer iris positioning method |
| CN105631407B (en) * | 2015-12-18 | 2018-12-11 | 电子科技大学 | Woods musk deer iris locating method |
| CN107871322A (en) * | 2016-09-27 | 2018-04-03 | 北京眼神科技有限公司 | Iris segmentation method and apparatus |
| CN107871322B (en) * | 2016-09-27 | 2020-08-28 | 北京眼神科技有限公司 | Iris image segmentation method and device |
| CN110647787A (en) * | 2018-06-27 | 2020-01-03 | 厦门本能管家科技有限公司 | Private key generation and decryption method and system based on iris recognition |
| CN111144413A (en) * | 2019-12-30 | 2020-05-12 | 福建天晴数码有限公司 | Iris positioning method and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2013087026A1 (en) | 2013-06-20 |
| CN102902970A (en) | 2013-01-30 |
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Application publication date: 20120627 |