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Research On The Methods Of Iris Recognition In The State Of Eyes Opening Unforcedly

Posted on:2009-04-17Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z H LinFull Text:PDF
GTID:1118360272499647Subject:Electrical theory and new technology
Abstract/Summary:PDF Full Text Request
With the constant development of modern technologies, traditional methods of personal recognition can not satisfy various demands of the present society. Under this condition, the personal recognition based on the biometric begins to develop rapidly. The rising biometrics has a lot of advantages which are not involved in traditional methods, such as high accuracy, high security, high reliability, and so on. Biometrics also satisfies many requirements of each field in our society. Iris recognition is an emerging biometric technology. For its exclusive, stability, collectible and unforced, iris recognition is being more and more regarded by people. In recent years, iris recognition has made progress in technology research and application, and has a wide prospect and market. Compared with face, voice, fingerprint and other biometric technology, iris recognition has higher precision.An iris recognition system includes iris imaging, iris preprocessing, feature extraction, pattern match and classifying. Its research aspects involve many subjects such as computer vision, digital image processing, wavelet theory, pattern recognition. Based on the recent advancements in iris recognition, this article makes discussion about iris localization, noise processing, normalization, feature extraction, code and classifying decision-making, and presents some improving methods and the experimental results are also described. These use for references for more research on the iris recognition technology.In iris localization, a method of iris localization based on the human eye structure is presented. Firstly, it removes the facula by the average gray of adjacent area and finds a point in the pupil by the projection and pupil-center detection operator, then finds four boundary points in inner and outer boundary respectively by edge detection operator or combining voting method to localize the inner and outer boundaries. Experimental results on 2655 eye images demonstrate that the proposed method of iris localization can effectively resolve the problems of iris translation and it can not be affected by facula, eyelid and eyelashes. Compared with two classical methods, the proposed method ensures the probability of successful localization and reduces the time consumedly.There is much noise in the state of eyes opening unforcedly, so the noise processing is necessary, the upper and lower eyelids are removed by parabola fitting, the facular is removed by neighboring gray average, the eyelashes are removed by finding all the candidate eyelashes by local gray minimum firstly, then the false eyelashes are removed by the beginning location, directional and length information of the eyelashes.In normalization, the annular iris image is normalized to rectangular image. It can resolve the problems of iris zoom and solve the disaccord of inner and outer center, and ensure the effective iris area for the next operations.In feature extraction and code, many feature extraction methods are presented such as based on wavelet transform coefficients, local gray minimum, texture feature points matching, multidirectional texture edge detection. The method based on the wavelet transform coefficients adopts Marr and Morlet wavelets to extract feature based on the wavelet transform coefficients, reviews the coefficients distribution of different scales. It can get feature of different frequency by setting different scale and analyze which iris texture proportion is higher under which scale. This method has more advantages, lower complication and higher recognition rate comparing with traditional wavelet transform methods. The method based on local gray minimum uses the position and gray information of iris texture, but discards other structure characteristic such as size, direction and relativity of texture, so the partial feature can not ensure to increase much more correctness. Although the method based on texture feature points matching uses the size and direction information, the direction information chosen is less and discards the relativity of texture, so there is much more elevated space. The method based on the multidirectional edge detection uses the position, gray, size, direction and relativity of texture, so the dividing features ensure to increase the precision much more.In pattern match and recognition, it calculates the distance between enroll iris code and register iris code by distance designed by ourselves, solves the rotary problems by many transferring matches along horizontal directions, and classifies by threshold.Finally the performance of the presented methods and the method based on the gabor filter is analyzed and compared in the V3 Interval database.
Keywords/Search Tags:Biometrics, Iris recognition, Edge detection, Structure characteristic, Wavelet transform coefficients
PDF Full Text Request
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