• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.227-230
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• 2002

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.233-238
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• 2005

With iris recognition algorithm, unique iris code can be generated and user can be identified by using iris pattern. However, if unnecessary information such as eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate ins code not excluding eyelash and the position of eyelash is moved, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelash by using mask and excluding the detected eyelash region in case of generating iris code. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.18\%$ compared to that not using it.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.268-273
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on local gradient orientation histogram which is robust to variations in illumination and rotations of iris patterns. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.128-134
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. because High-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system using iris feature extraction methods have implement. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.322-326
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• 2004

This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.48-60
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• 2007

In previous researches for iris feature extraction, they transform a original iris image into rectangular one by stretching and interpolation, which causes the distortion of iris patterns. Consequently, it reduce iris recognition accuracy. So we are propose the method that extracts iris feature by using polar coordinates without distortion of iris patterns. Our proposed method has three strengths compared with previous researches. First, we extract iris feature directly from polar coordinate circular iris image. Though it requires a little more processing time, there is no degradation of accuracy for iris recognition and we compares the recognition performance of polar coordinate to rectangular type using by Hamming Distance, Cosine Distance and Euclidean Distance. Second, in general, the center position of pupil is different from that of iris due to camera angle, head position and gaze direction of user. So, we propose the method of iris feature detection based on polar coordinate circular iris region, which uses pupil and iris position and radius at the same time. Third, we overcome override point from iris patterns by using polar coordinates circular method. each overlapped point would be extracted from the same position of iris region. To overcome such problem, we modify Gabor filter's size and frequency on first track in order to consider low frequency iris patterns caused by overlapped points. Experimental results showed that EER is 0.29%, d' is 5,9 and EER is 0.16%, d' is 6,4 in case of using conventional rectangular image and proposed method, respectively.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.421-428
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• 2004

There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.121-128
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, iris information is used in many fields such as access control and information security. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil. In this paper, we propose a novel method based on vector summation of gradient orientation vectors. Experimental results show that the proposed method reduces processing time with simple vector calculation, requires small feature space and has comparable performance to the well-known previous methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.31-40
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• 2012

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on Zernike Moment which is robust to rotations of iris patterns. we utilized a selection of Zernike moments for the fast and effective recognition by selecting global optimum moments and local optimum moments for optimal matching of each iris class. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.169-174
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• 2008

Recently, biometric systems are of interest for the reliable security system. Iris recognition technology is one of the biometric system with the highest reliability. Various iris recognition methods have been proposed for automatic personal identification and verification. These methods require accurate iris segmentation for successful processing because the iris is a small part of an acquired image. The iris boundaries have been parametrically modeled and subsequently detected by circles or parabolic arcs. Since the iris boundaries have a wide range of edge contrast and irregular border shapes, the assumption that they can be fit to circles or parabolic arcs is not always valid. In some cases, the shape of a dilated pupil is slightly different from a constricted one. This is especially true when the pupil has an irregular shape. This is why this research is important. This paper addresses how to accurately detect iris boundaries for improved iris recognition, which is robust to noises.