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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Main Authors: Cheng-Yu Weng, 翁正宇
Other Authors: Shuenn-Shyang Wang
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/02499255369925203153
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spelling 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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description 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.
author2 Shuenn-Shyang Wang
author_facet Shuenn-Shyang Wang
Cheng-Yu Weng
翁正宇
author Cheng-Yu Weng
翁正宇
spellingShingle Cheng-Yu Weng
翁正宇
Adaptive Object Detection Using Fuzzy System for Environment Change
author_sort 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
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