The effect of sub-sampling in scale space texture classification using combined classifiers
Textures show multi-scale properties and hence multiresolution techniques are considered appropriate for texture classification. Recently, the authors proposed a multiresolution texture classification system based on scale space theory and combined classifiers. However, the use of multiresolution te...
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| creator | Gangeh, M.J. ter Haar Romeny, B.M. Eswaran, C. |
| description | Textures show multi-scale properties and hence multiresolution techniques are considered appropriate for texture classification. Recently, the authors proposed a multiresolution texture classification system based on scale space theory and combined classifiers. However, the use of multiresolution techniques increases the computational load and memory space required. Sub-sampling can help to reduce these side effects of multiresolution techniques. However, it may degrade the overall performance of the classification system. In this paper the effect of sub-sampling is investigated in scale space texture classification using combined classifiers. It is shown that sub-sampling can help to reduce both computational load and memory space required without compromising the performance of the system. |
| doi_str_mv | 10.1109/ICIAS.2007.4658498 |
| format | Conference Proceeding |
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It is shown that sub-sampling can help to reduce both computational load and memory space required without compromising the performance of the system.</description><subject>Artificial intelligence</subject><subject>Energy resolution</subject><subject>Feature extraction</subject><subject>Memory management</subject><subject>Multimedia communication</subject><subject>Principal component analysis</subject><subject>Training</subject><isbn>9781424413553</isbn><isbn>1424413559</isbn><isbn>9781424413560</isbn><isbn>1424413567</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkEtLw0AcxFekoNZ8Ab3sF0jc9-NYgtpAwYP15KFsNv_VlbzIJqDfXotFcC7DMD_mMAjdUFJQSuxdVVab54IRoguhpBHWnKHMakMFE4Jyqcj5vyz5Cl0dccuM4vQCZSl9kB9xKwVhl-h1_w4YQgA_4yHgtNR5ct3Yxv4Nxx4n71rAaXQe8Ayf8zIB9q1LKYbo3RyHHi_pyPqhq2MPzV8LU7pGq-DaBNnJ1-jl4X5fbvPd02NVbnZ5pFrOuTOUKSmshSAYJzqQAJpIZVVw4F2jjQs1NYQ24L3nRnNlKfe1oAac4pyv0e3vbgSAwzjFzk1fh9M__BtRWVfR</recordid><startdate>200711</startdate><enddate>200711</enddate><creator>Gangeh, M.J.</creator><creator>ter Haar Romeny, B.M.</creator><creator>Eswaran, C.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200711</creationdate><title>The effect of sub-sampling in scale space texture classification using combined classifiers</title><author>Gangeh, M.J. ; ter Haar Romeny, B.M. ; Eswaran, C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-a81265499ef42307f0fe705696faecad78afb1801deccc38736913cb418ea6333</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Artificial intelligence</topic><topic>Energy resolution</topic><topic>Feature extraction</topic><topic>Memory management</topic><topic>Multimedia communication</topic><topic>Principal component analysis</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Gangeh, M.J.</creatorcontrib><creatorcontrib>ter Haar Romeny, B.M.</creatorcontrib><creatorcontrib>Eswaran, C.</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 Electronic Library (IEL)</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>Gangeh, M.J.</au><au>ter Haar Romeny, B.M.</au><au>Eswaran, C.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>The effect of sub-sampling in scale space texture classification using combined classifiers</atitle><btitle>2007 International Conference on Intelligent and Advanced Systems</btitle><stitle>ICIAS</stitle><date>2007-11</date><risdate>2007</risdate><spage>806</spage><epage>809</epage><pages>806-809</pages><isbn>9781424413553</isbn><isbn>1424413559</isbn><eisbn>9781424413560</eisbn><eisbn>1424413567</eisbn><abstract>Textures show multi-scale properties and hence multiresolution techniques are considered appropriate for texture classification. 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| subjects | Artificial intelligence Energy resolution Feature extraction Memory management Multimedia communication Principal component analysis Training |
| title | The effect of sub-sampling in scale space texture classification using combined classifiers |
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