Adaptive Object Detection Using Fuzzy System for Environment Change
碩士 === 大同大學 === 通訊工程研究所 === 101 === Background subtraction is an essential technique for automatic video analysis. To improve the accuracy of background subtraction in the dark environment and the light illumination changing environment, a new algorithm of adaptive background building and foreground...
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ndltd-TW-101TTU056500102015-10-13T22:52:06Z http://ndltd.ncl.edu.tw/handle/02499255369925203153 Adaptive Object Detection Using Fuzzy System for Environment Change 基於模糊理論之自適應環境變化物件偵測 Cheng-Yu Weng 翁正宇 碩士 大同大學 通訊工程研究所 101 Background subtraction is an essential technique for automatic video analysis. To improve the accuracy of background subtraction in the dark environment and the light illumination changing environment, a new algorithm of adaptive background building and foreground detection based on fuzzy system has been proposed in the thesis. We apply fuzzy rules to classify the input image to 5 classes and then set the appropriate image weight for each class. In this way, the image information between bright and dusky environment will do not interfere with each other. The proposed texture feature is based on local binary pattern (LBP), while the color feature is represented by HSI color space. The experimental results show that the proposed algorithm can correctly detect the foreground in dark environment and light illumination changing environment. Shuenn-Shyang Wang 汪順祥 2013 學位論文 ; thesis 46 en_US |
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碩士 === 大同大學 === 通訊工程研究所 === 101 === Background subtraction is an essential technique for automatic video analysis. To improve the accuracy of background subtraction in the dark environment and the light illumination changing environment, a new algorithm of adaptive background building and foreground detection based on fuzzy system has been proposed in the thesis. We apply fuzzy rules to classify the input image to 5 classes and then set the appropriate image weight for each class. In this way, the image information between bright and dusky environment will do not interfere with each other. The proposed texture feature is based on local binary pattern (LBP), while the color feature is represented by HSI color space. The experimental results show that the proposed algorithm can correctly detect the foreground in dark environment and light illumination changing environment.
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Shuenn-Shyang Wang |
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Shuenn-Shyang Wang Cheng-Yu Weng 翁正宇 |
author |
Cheng-Yu Weng 翁正宇 |
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Cheng-Yu Weng 翁正宇 Adaptive Object Detection Using Fuzzy System for Environment Change |
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Cheng-Yu Weng |
title |
Adaptive Object Detection Using Fuzzy System for Environment Change |
title_short |
Adaptive Object Detection Using Fuzzy System for Environment Change |
title_full |
Adaptive Object Detection Using Fuzzy System for Environment Change |
title_fullStr |
Adaptive Object Detection Using Fuzzy System for Environment Change |
title_full_unstemmed |
Adaptive Object Detection Using Fuzzy System for Environment Change |
title_sort |
adaptive object detection using fuzzy system for environment change |
publishDate |
2013 |
url |
http://ndltd.ncl.edu.tw/handle/02499255369925203153 |
work_keys_str_mv |
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