توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Novel High Performance Iris and Pupil Localization Method
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس ماشین بینایی و پردازش تصویر، سال
تعداد صفحات: ۵
Iris detection is a computationally intensive task in the overall iris biometric processing. In this paper we proposed a technique to localize the iris and the pupil in eye images efficiently and accurately. This paper includes three stages: The first stage is related to finding the centre and radius of pupil. In this stage, the problem of pupil non–uniformity which may appear in some images is solved and the pupil is detected. In the second stage a new approach, based on circular arc search, is proposed to extract iris boundary. The last stage includes wavelet–based feature extraction and classifier design. Our approach has been applied on the CASIA standard database. High accuracy of the proposed iris localization method resulted in a high performance iris recognition system<\div>

۲A Novel Clustering Method Using PSO–Adjusted Space Conversion
نویسنده(ها): ،
اطلاعات انتشار: دومین کنگره مشترک سیستم های فازی و سیستم های هوشمند، سال
تعداد صفحات: ۸
Conventional clustering methods may fail to solve some real world clustering problems. In this paper, a novel clustering method using PSO–adjustedspace conversion is presented. The main idea of proposed algorithm is to transfer given dataset to a new space in witch conventional clustering methodscan determine the intrinsic grouping in the set. Finding such a linear transform that would result in minimum error and precise clustering is performed by particleswarm optimization (PSO). The merit of proposed method is certificated in skin detection as a real word benchmark problem<\div>
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