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A New Approach for Image Thresholding under Uneven Lighting Conditions
Image thresholding is a useful method in many image processing and computer vision applications. However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this pap...
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creator | Yao-Hong Tsai |
description | Image thresholding is a useful method in many image processing and computer vision applications. However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this paper, we propose a novel method for adaptive local thresholding by applying Otsu's results. Based on simulated annealing, the proposed algorithm searches the optimal threshold for each partitioned subimage according to the quadtree data structure. It is also scale invariant for different object sizes. For reducing the computations, an improvement of Otsu 's method is also developed. Experimental results show the efficiency of the proposed method. |
doi_str_mv | 10.1109/ICIS.2007.32 |
format | conference_proceeding |
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However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this paper, we propose a novel method for adaptive local thresholding by applying Otsu's results. Based on simulated annealing, the proposed algorithm searches the optimal threshold for each partitioned subimage according to the quadtree data structure. It is also scale invariant for different object sizes. For reducing the computations, an improvement of Otsu 's method is also developed. 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However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this paper, we propose a novel method for adaptive local thresholding by applying Otsu's results. Based on simulated annealing, the proposed algorithm searches the optimal threshold for each partitioned subimage according to the quadtree data structure. It is also scale invariant for different object sizes. For reducing the computations, an improvement of Otsu 's method is also developed. Experimental results show the efficiency of the proposed method.</description><subject>Application software</subject><subject>Brightness</subject><subject>Computational complexity</subject><subject>Computational modeling</subject><subject>Computer science</subject><subject>Computer vision</subject><subject>Histograms</subject><subject>Image processing</subject><subject>Image segmentation</subject><subject>Lighting</subject><isbn>0769528414</isbn><isbn>9780769528410</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjM1KxDAURgMiqOPs3LnJC7Tmr7nNshRHC0UXzqyHpLltIzNpSUfFt3dEv82Bw-Ej5I6znHNmHpq6ecsFY5BLcUFuGGhTiFJxdUXWy_LOzpNGMSivyaaiL_hFq3lOk-1G2k-JNkc7IN2OCZdxOvgQB_oRPSa6i_iJkbZhGE-_tp6iD6cwxeWWXPb2sOD6nyuy2zxu6-esfX1q6qrNAofilDkP4FyBnhWqtAak5p1GD72yneDKaWV6AdY7cJ3orVHWGONRnTsrhSjkitz__QZE3M8pHG363isBWupS_gCEwkio</recordid><startdate>200707</startdate><enddate>200707</enddate><creator>Yao-Hong Tsai</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200707</creationdate><title>A New Approach for Image Thresholding under Uneven Lighting Conditions</title><author>Yao-Hong Tsai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-bd77bb5ed0548a97361c6ed7f4ac214b649f27adb7bc2fa94a999de4361a32253</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Application software</topic><topic>Brightness</topic><topic>Computational complexity</topic><topic>Computational modeling</topic><topic>Computer science</topic><topic>Computer vision</topic><topic>Histograms</topic><topic>Image processing</topic><topic>Image segmentation</topic><topic>Lighting</topic><toplevel>online_resources</toplevel><creatorcontrib>Yao-Hong Tsai</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yao-Hong Tsai</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A New Approach for Image Thresholding under Uneven Lighting Conditions</atitle><btitle>6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007)</btitle><stitle>ICIS</stitle><date>2007-07</date><risdate>2007</risdate><spage>123</spage><epage>127</epage><pages>123-127</pages><isbn>0769528414</isbn><isbn>9780769528410</isbn><abstract>Image thresholding is a useful method in many image processing and computer vision applications. However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this paper, we propose a novel method for adaptive local thresholding by applying Otsu's results. Based on simulated annealing, the proposed algorithm searches the optimal threshold for each partitioned subimage according to the quadtree data structure. It is also scale invariant for different object sizes. For reducing the computations, an improvement of Otsu 's method is also developed. Experimental results show the efficiency of the proposed method.</abstract><pub>IEEE</pub><doi>10.1109/ICIS.2007.32</doi><tpages>5</tpages></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Application software Brightness Computational complexity Computational modeling Computer science Computer vision Histograms Image processing Image segmentation Lighting |
title | A New Approach for Image Thresholding under Uneven Lighting Conditions |
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