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

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.438-456
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• 2010

Iris recognition uses a unique iris pattern of user to identify person. In order to enhance the performance of iris recognition, it is reported that the diameter of iris region should be greater than 200 pixels in the captured iris image. So, the previous iris system used zoom lens camera, which can increase the size and cost of system. To overcome these problems, we propose a new method of enhancing the accuracy of iris recognition on low-resolution iris images which are captured without a zoom lens. This research is novel in the following two ways compared to previous works. First, this research is the first one to analyze the performance degradation of iris recognition according to the decrease of the image resolution by excluding other factors such as image blurring and the occlusion of eyelid and eyelash. Second, in order to restore a high-resolution iris image from single low-resolution one, we propose a new method based on multiple multi-layered perceptrons (MLPs) which are trained according to the edge direction of iris patterns. From that, the accuracy of iris recognition with the restored images was much enhanced. Experimental results showed that when the iris images down-sampled by 6% compared to the original image were restored into the high resolution ones by using the proposed method, the EER of iris recognition was reduced as much as 0.133% (1.485% - 1.352%) in comparison with that by using bi-linear interpolation

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

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.2
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• pp.29-34
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• 2012

Purpose : Presently, hardwares and softwares for reducing radiation exposure are continually developed for PET/CT examination. Purpose of this study is to evaluate effectiveness of reducing radiation exposure dose of CT and SUV changes of PET when applied each kernel to ACCT (Attenuation Correction Computed Tomography) according to adopted IRIS (Iterative Reconstruction in Image Space) software. Materials and Methods : Biograph mCT (Siemens, Germany) was used as a PET/CT scanner. Using AAPM CT performance phantom, from standard (120 kVp, 100 mAs), 7 scans were conducted by reducing 15 mAs each. After image reconstruction by FBP (Filtered Back Projection) and IRIS, noise and spatial resolution were evaluated. The same method was applied to anthropomorphic chest phantom and acquired images were compared. NEMA IEC body phantom was used for SUV evaluation. Injected dose rate for hot sphere (hot) and background cylinder (BKG) were 1:8. CT dose condition (120 kVp, 50 mAs) was the same for each scan and PET scan durations were 1, 2, 3 and 4min. After scanning, each kernel of IRIS was applied to ACCT. And PET images were reconstructed by ACCT adopted IRIS for comparing SUV changes. Results : AAPM phantom test for noise evaluation, SD for FBP 100 mAs, IRIS 55 mAs were 8.8 and 8.9. FBP 85 mAs, IRIS 40 mAs were 9.5 and 9.7. FBP 70 mAs, IRIS 25 mAs were 11.9 and 11.1. Above mAs condition for FBP and IRIS, SD showed similar values. And for spatial resolution test, there was no significant difference. For chest phantom test, when applied the same mAs and kernel to both of FBP and IRIS, every applied kernels showed reduced noise. Lower mAs and higher kernel value showed higher noise reduction. There was no considerable difference only except for I70 very sharp kernel for SUV comparison using NEMA IEC body phantom. Conclusion : In this study, low mAs (55 mAs) applied IRIS and standard mAs (100 mAs) applied FBP showed similar noise. And only except for I70 kernel, there was no significant SUV changes. It is possible to reduce needless radiation exposure and acquire better image quality than FBP's through applying appropriate kernel of IRIS to PET/CT.