Co-occurrence features of multi-scale directional filter bank for texture characterization
In this paper, we propose to use co-occurrence features computed from multi-scale directional filter bank (MDFB) for texture characterization. As the filter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textu...
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| creator | Cheng, K.O. Law, N.F. Siu, W.C. |
| description | In this paper, we propose to use co-occurrence features computed from multi-scale directional filter bank (MDFB) for texture characterization. As the filter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintains a high retrieval rate for regular textures as the energy features |
| doi_str_mv | 10.1109/ISCAS.2006.1693879 |
| format | Conference Proceeding |
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In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintains a high retrieval rate for regular textures as the energy features</description><identifier>ISSN: 0271-4302</identifier><identifier>ISBN: 0780393899</identifier><identifier>ISBN: 9780780393899</identifier><identifier>EISSN: 2158-1525</identifier><identifier>DOI: 10.1109/ISCAS.2006.1693879</identifier><language>eng</language><publisher>IEEE</publisher><subject>Band pass filters ; Energy resolution ; Feature extraction ; Filter bank ; Frequency ; Image databases ; Image retrieval ; Image storage ; Signal processing ; Wavelet coefficients</subject><ispartof>2006 IEEE International Symposium on Circuits and Systems (ISCAS), 2006, p.4 pp.-5502</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1693879$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,4035,4036,27904,54899</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1693879$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Cheng, K.O.</creatorcontrib><creatorcontrib>Law, N.F.</creatorcontrib><creatorcontrib>Siu, W.C.</creatorcontrib><title>Co-occurrence features of multi-scale directional filter bank for texture characterization</title><title>2006 IEEE International Symposium on Circuits and Systems (ISCAS)</title><addtitle>ISCAS</addtitle><description>In this paper, we propose to use co-occurrence features computed from multi-scale directional filter bank (MDFB) for texture characterization. As the filter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintains a high retrieval rate for regular textures as the energy features</description><subject>Band pass filters</subject><subject>Energy resolution</subject><subject>Feature extraction</subject><subject>Filter bank</subject><subject>Frequency</subject><subject>Image databases</subject><subject>Image retrieval</subject><subject>Image storage</subject><subject>Signal processing</subject><subject>Wavelet coefficients</subject><issn>0271-4302</issn><issn>2158-1525</issn><isbn>0780393899</isbn><isbn>9780780393899</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9js1OwzAQhFf8SAToC8DFL-CwdpomPqIIVM7l1EvlmrUwuDFaOxLw9KRSz8xlNPpmpAG4U1grhebhZTM8bmqNuKrVyjR9Z86g0qrtpWp1ew7X2PXYzMCYC6hQd0ouG9RXsMj5A2ct2zljBdshyeTcxEyjI-HJlokpi-TFYYolyOxsJPEWmFwJabRR-BALsdjb8VP4xKLQ93Ej3Ltl62YUfu2xeguX3sZMi5PfwP3z0-uwloGIdl8cDpZ_dqf7zf_0D89UR2c</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Cheng, K.O.</creator><creator>Law, N.F.</creator><creator>Siu, W.C.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2006</creationdate><title>Co-occurrence features of multi-scale directional filter bank for texture characterization</title><author>Cheng, K.O. ; Law, N.F. ; Siu, W.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_16938793</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Band pass filters</topic><topic>Energy resolution</topic><topic>Feature extraction</topic><topic>Filter bank</topic><topic>Frequency</topic><topic>Image databases</topic><topic>Image retrieval</topic><topic>Image storage</topic><topic>Signal processing</topic><topic>Wavelet coefficients</topic><toplevel>online_resources</toplevel><creatorcontrib>Cheng, K.O.</creatorcontrib><creatorcontrib>Law, N.F.</creatorcontrib><creatorcontrib>Siu, W.C.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cheng, K.O.</au><au>Law, N.F.</au><au>Siu, W.C.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Co-occurrence features of multi-scale directional filter bank for texture characterization</atitle><btitle>2006 IEEE International Symposium on Circuits and Systems (ISCAS)</btitle><stitle>ISCAS</stitle><date>2006</date><risdate>2006</risdate><spage>4 pp.</spage><epage>5502</epage><pages>4 pp.-5502</pages><issn>0271-4302</issn><eissn>2158-1525</eissn><isbn>0780393899</isbn><isbn>9780780393899</isbn><abstract>In this paper, we propose to use co-occurrence features computed from multi-scale directional filter bank (MDFB) for texture characterization. As the filter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintains a high retrieval rate for regular textures as the energy features</abstract><pub>IEEE</pub><doi>10.1109/ISCAS.2006.1693879</doi></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Band pass filters Energy resolution Feature extraction Filter bank Frequency Image databases Image retrieval Image storage Signal processing Wavelet coefficients |
| title | Co-occurrence features of multi-scale directional filter bank for texture characterization |
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