• Journal of Digital Contents Society
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• v.2 no.2
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• pp.179-189
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• 2001

This paper aims at faster processing and retrieval in fingerprint identification systems by reducing the amount of preprocessing and the size of the feature vector. The distribution of fingerprint directions is a set of local directions of ridges and furrows in small overlapped blocks in a fingerprint image. It is extracted initially as a set of 8-direction components through the Gabor filter bank. The discontinuous distribution of directions is smoothed to a continuous one and visualized as a direction image. Then the center of the distribution is selected as a reference point. A feature vector is composed of 192 sine values of the ridge angles at 32-equiangular positions with 6 different distances from the reference point in the direction image. Experiments show that the proposed algorithm performs the same level of correct identification as a conventional algorithm does, while speeding up the overall processing significantly by reducing the length of the feature vector.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.70-76
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• 2002

In this paper, we proposed a personal identification algorithm using the iris region which has discriminant features. First, we acquired the eye image with the black and white CCD camera and extracted the iris region by using a circular edge detector which minimizes the search space for real center and radius of the iris. And then, we localized the iris region into several circles and extracted the features by filtering signals on the perimeters of circles with one dimensional Gabor filter We identified a person by comparing ,correlation values of input signals with the registered signals. We also decided threshold value minimizing average error rate for FRR(Type I)error rate and FAR(Type II)error rate. Experimental results show that proposed algorithm has average error rate less than 5.2%.

• 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.