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Anti-Spoof Reliable Biometry of Fingerprints Using <i>En-Face</i>Optical Coherence Tomography 被引量:3
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作者 Mohammad-Reza Nasiri-Avanaki Alexander Meadway +3 位作者 Adrian Bradu Rohollah Mazrae Khoshki ali hojjatoleslami Adrian Gh. Podoleanu 《Optics and Photonics Journal》 2011年第3期91-96,共6页
Optical coherence tomography (OCT) is a relatively new imaging technology which can produce high resolution images of three-dimensional structures. OCT has been mainly used for medical applications such as for ophthal... Optical coherence tomography (OCT) is a relatively new imaging technology which can produce high resolution images of three-dimensional structures. OCT has been mainly used for medical applications such as for ophthalmology and dermatology. In this study we demonstrate its capability in providing much more reliable biometry identification of fingerprints than conventional methods. We prove that OCT can serve secure control of genuine fingerprints as it can detect if extra layers are placed above the finger. This can prevent with a high probability, intruders to a secure area trying to foul standard systems based on imaging the finger surface. En-Face OCT method is employed and recommended for its capability of providing not only the axial succession of layers in depth, but the en-face image that allows the traditional pattern identification. Another reason for using such OCT technology is that it is compatible with dynamic focus and therefore can provide enhanced transversal resolution and sensitivity. Two En-Face OCT systems are used to evaluate the need for high resolution and conclusions are drawn in terms of the most potential commercial route to ex- ploitation. 展开更多
关键词 Optical Coherence Tomography En-Face OCT FINGERPRINTS BIOMETRY High Resolution
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Brain tissue segmentation based on spatial information fusion by Dempster-Shafer theory
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作者 Jamal GHASEMI Mohammad Reza KARAMI MOLLAEI +1 位作者 Reza GHADERI ali hojjatoleslami 《Journal of Zhejiang University-Science C(Computers and Electronics)》 SCIE EI 2012年第7期520-533,共14页
As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented whi... As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented which employs Dempster-Shafer theory (DST) to perform information fusion.In the proposed method,fuzzy c-mean (FCM) is applied to separate features and then the outputs of FCM are interpreted as basic belief structures.The salient aspect of this paper is the interpretation of each FCM output as a belief structure with particular focal elements.The results of the proposed method are evaluated using Dice similarity and Accuracy indices.Qualitative and quantitative comparisons show that our method performs better and is more robust than the existing method. 展开更多
关键词 Magnetic resonance imaging (MR/) SEGMENTATION Fuzzy c-mean (FCM) Dempster-Shafer theory (DST)
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