• Journal of the Korea Society of Computer and Information
• /
• v.24 no.2
• /
• pp.35-40
• /
• 2019

In this paper, we propose a technique to reconstruct the iris image from the iris code by analyzing the process of generating the iris code and calculating it inversely. Iris recognition is an authentication method for authenticating an individual's identity by using iris information of an eye having unique information of an individual. The iris recognition extracts the features of the iris from the iris image, creates the iris code, and determines whether to authenticate using the corresponding code. The iris recognition method using the iris code is a method proposed by Daugman for the first time and is widely used as a representative method of iris recognition technology currently used commercially. In this paper, we restore the iris image with only the iris code, and test whether the reconstructed image and the original image can be recognized, and analyze restoration vulnerability of Daugman's iris code.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.287-288
• /
• 2007

In this paper, we propose a fake-iris detection method. In order to detect the fake-iris, we measure physiological features which are the reflectance ratio of the iris to the sclera at 750 nm and that at 850nm. In order to classify live and fake iris features, we use support vector data description (SVDD). From our experimental results, it is clear that our fake-iris detection method achieves high performance when distinguishing between a live-iris and a fake-iris.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.351-354
• /
• 2005

In this paper, we propose a new fake-iris detection method. In order to detect the fake-iris, we measure the change of the reflectance ratio between iris and sclera. In a live iris, the amount of change is relatively large compared to that in a fake-iris. From our experimental results, it is clear that our fake-iris detection method achieves high performance when distinguishing between a live-iris and a fake-iris.

• ETRI Journal
• /
• v.29 no.3
• /
• pp.399-401
• /
• 2007

With a growing emphasis on human identification, iris recognition has recently received increasing attention. Iris recognition includes eye imaging, iris segmentation, verification, and so on. In this letter, we propose a novel and efficient iris recognition method which employs a cumulative-sum-based grey change analysis. Experimental results demonstrate that the proposed method can be used for human identification in efficient manner.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.392-395
• /
• 2003

This paper describes a new iris segmentation and recognition method, which is robust to noises. Combining statistical classification and elastic boundary fitting, the iris is first segmented. Then, the localized iris image is smoothed by a convolution with a Gaussian function, down-sampled by a factor of filtered with a Laplacian operator, and quantized using the Lloyd-Max method. Since the quantized output is sensitive to a small shift of the full-resolution iris image, the outputs of the Laplacian operator are computed for all space shifts. The quantized output with maximum entropy is selected as the final feature representation. An appropriate formulation of similarity measure is defined for the classification of the quantized output. Experimentally we showed that the proposed method produces superb performance in iris segmentation and recognition.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.178-186
• /
• 2003

Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.321-322
• /
• 2006

In this paper, we propose a method that extracts invariant iris codes from user's iris pattern in order to apply these codes to a new cryptographic construct called fuzzy vault. The fuzzy vault, proposed by Juels and Sudan, has been used to manage cryptographic key safely by merging with biometrics. Generally, iris data has intra-variation of iris pattern according to sensed environmental changes, but cryptography requires correctness. Therefore, to combine iris data and fuzzy vault, we have to extract an invariant iris feature from iris pattern. In this paper, we obtain invariant iris codes by clustering iris features extracted by independent component analysis(ICA) transform. From experimental results, we proved that the iris codes extracted by our method are invariant to sensed environmental changes and can be used in fuzzy vault.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.3
• /
• pp.48-60
• /
• 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 Journal of the Korea Contents Association
• /
• v.5 no.5
• /
• pp.59-64
• /
• 2005

The biometrics of iris is a very accurate authentication method. The biometrics of iris can recognize and identify a person for shortly. But the image of iris is changed by transformation of body in the life. The existing iris authentication system has problem that can be mis-recognized. In this paper, we proposed and implemented Renewable Iris Authentication Algorithm(RIAA) for biometrics in authentication system. This algorithm tries to present a new way to people identification, we show contour line when shift take photograph in regular side. Namely, it generate iris code based on boundary of projection or submergence side and compared to original, so that it describes iris identification method to people identification.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.2
• /
• pp.117-137
• /
• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.