Automatic ear recognition under varying illumination / Ali Abd Almisreb
Recognition systems grow rapidly and there are many recognition systems that have been investigated such as iris systems, fingerprint systems, face detection systems and many others, bi this thesis, we created ear database under variant distances and illumination environment consisting of 200 images...
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2012
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my.uitm.ir.872352024-02-24T17:50:31Z https://ir.uitm.edu.my/id/eprint/87235/ Automatic ear recognition under varying illumination / Ali Abd Almisreb Abd Almisreb, Ali Back propagation (Artificial intelligence) TA Engineering. Civil engineering Recognition systems grow rapidly and there are many recognition systems that have been investigated such as iris systems, fingerprint systems, face detection systems and many others, bi this thesis, we created ear database under variant distances and illumination environment consisting of 200 images from fifty persons. In addition, we identified a new ear segmentation approach which is able to extract the ear section despite of the distance and illumination of the captured ear image. The processes to segment the ear sections are Biased Normalized Cote, image adjustment, entropy, thresholding, skeletonizing, image filling, image opening and substitution. Then, we enhanced the ear recognition rate. For feature extraction, we used ID log- Gabor filter to generate an ear code and hamming distance is utilized as matching algorithm. Subjective evaluations showed that our proposed system managed to achieve 95% &r ear segmentation rate and 96.662% for ear recognition rate. 2012 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/87235/1/87235.pdf Automatic ear recognition under varying illumination / Ali Abd Almisreb. (2012) Masters thesis, thesis, Universiti Teknologi MARA (UiTM). |
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Back propagation (Artificial intelligence) TA Engineering. Civil engineering Abd Almisreb, Ali Automatic ear recognition under varying illumination / Ali Abd Almisreb |
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Recognition systems grow rapidly and there are many recognition systems that have been investigated such as iris systems, fingerprint systems, face detection systems and many others, bi this thesis, we created ear database under variant distances and illumination environment consisting of 200 images from fifty persons. In addition, we identified a new ear segmentation approach which is able to extract the ear section despite of the distance and illumination of the captured ear image. The processes to segment the ear sections are Biased Normalized Cote, image adjustment, entropy, thresholding, skeletonizing, image filling, image opening and substitution. Then, we enhanced the ear recognition rate. For feature extraction, we used ID log- Gabor filter to generate an ear code and hamming distance is utilized as matching algorithm. Subjective evaluations showed that our proposed system managed to achieve 95% &r ear segmentation rate and 96.662% for ear recognition rate. |
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Thesis |
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Abd Almisreb, Ali |
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Abd Almisreb, Ali |
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Abd Almisreb, Ali |
title |
Automatic ear recognition under varying illumination / Ali Abd Almisreb |
title_short |
Automatic ear recognition under varying illumination / Ali Abd Almisreb |
title_full |
Automatic ear recognition under varying illumination / Ali Abd Almisreb |
title_fullStr |
Automatic ear recognition under varying illumination / Ali Abd Almisreb |
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Automatic ear recognition under varying illumination / Ali Abd Almisreb |
title_sort |
automatic ear recognition under varying illumination / ali abd almisreb |
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2012 |
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https://ir.uitm.edu.my/id/eprint/87235/1/87235.pdf https://ir.uitm.edu.my/id/eprint/87235/ |
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