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Building Change Detection by Histogram Classification
This paper presents a supervised classification method applied to building change detection in VHR aerial images. Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose...
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| creator | Beumier, C. Idrissa, M. |
| description | This paper presents a supervised classification method applied to building change detection in VHR aerial images. Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose bins finally hold the ratio of built-up and non built-up pixels, according to the vector database to be updated. This ratio is used as building confidence at each pixel to issue a building confidence map from which to perform building verification and detection. The implementation based on histogram is very simple to code, very fast in execution and compares in this application to a state-of-the-art supervised classifier. It has been tested for the Belgian National Mapping Agency (IGN) to identify areas with high probability of change in building layers. |
| doi_str_mv | 10.1109/SITIS.2011.27 |
| format | conference_proceeding |
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Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose bins finally hold the ratio of built-up and non built-up pixels, according to the vector database to be updated. This ratio is used as building confidence at each pixel to issue a building confidence map from which to perform building verification and detection. The implementation based on histogram is very simple to code, very fast in execution and compares in this application to a state-of-the-art supervised classifier. It has been tested for the Belgian National Mapping Agency (IGN) to identify areas with high probability of change in building layers.</description><subject>Building change detection</subject><subject>Buildings</subject><subject>Digital Surface Model</subject><subject>histogram classification</subject><subject>Histograms</subject><subject>Image color analysis</subject><subject>multi-spectral images</subject><subject>Support vector machine classification</subject><subject>Three dimensional displays</subject><subject>Vegetation mapping</subject><isbn>146730431X</isbn><isbn>9781467304313</isbn><isbn>9780769546353</isbn><isbn>0769546358</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjD1PwzAUAI0QElAyMrH4DyT4-eM5HiFQGqkSQzOwVY7zEozSFMVh6L8HBLfccNIxdguiABDuflc39a6QAqCQ9oxlzpbCojMalVHn7Bo0WiW0grdLlqX0IX5AdKWGK2Yev-LYxWng1bufBuJPtFBY4nHi7YlvYlqOw-wPvBp9SrGPwf-2G3bR-zFR9u8Va9bPTbXJt68vdfWwzaMTS952iqRUIXSkQRgny4CI0gqreiRDQSO1JvQ-SIWlbZXzYCBA22HnjQW1Ynd_20hE-885Hvx82iNIgaVQ3zaURZM</recordid><startdate>201111</startdate><enddate>201111</enddate><creator>Beumier, C.</creator><creator>Idrissa, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201111</creationdate><title>Building Change Detection by Histogram Classification</title><author>Beumier, C. ; Idrissa, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-bd3e223ccde4105928c66627073f6e5ec46eb5cfac23687b39a151c1bd6da5713</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Building change detection</topic><topic>Buildings</topic><topic>Digital Surface Model</topic><topic>histogram classification</topic><topic>Histograms</topic><topic>Image color analysis</topic><topic>multi-spectral images</topic><topic>Support vector machine classification</topic><topic>Three dimensional displays</topic><topic>Vegetation mapping</topic><toplevel>online_resources</toplevel><creatorcontrib>Beumier, C.</creatorcontrib><creatorcontrib>Idrissa, M.</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 Xplore</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>Beumier, C.</au><au>Idrissa, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Building Change Detection by Histogram Classification</atitle><btitle>2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems</btitle><stitle>sitis</stitle><date>2011-11</date><risdate>2011</risdate><spage>409</spage><epage>415</epage><pages>409-415</pages><isbn>146730431X</isbn><isbn>9781467304313</isbn><eisbn>9780769546353</eisbn><eisbn>0769546358</eisbn><abstract>This paper presents a supervised classification method applied to building change detection in VHR aerial images. Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose bins finally hold the ratio of built-up and non built-up pixels, according to the vector database to be updated. This ratio is used as building confidence at each pixel to issue a building confidence map from which to perform building verification and detection. The implementation based on histogram is very simple to code, very fast in execution and compares in this application to a state-of-the-art supervised classifier. It has been tested for the Belgian National Mapping Agency (IGN) to identify areas with high probability of change in building layers.</abstract><pub>IEEE</pub><doi>10.1109/SITIS.2011.27</doi><tpages>7</tpages></addata></record> |
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| identifier | ISBN: 146730431X |
| ispartof | 2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems, 2011, p.409-415 |
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| language | eng |
| recordid | cdi_ieee_primary_6120680 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Building change detection Buildings Digital Surface Model histogram classification Histograms Image color analysis multi-spectral images Support vector machine classification Three dimensional displays Vegetation mapping |
| title | Building Change Detection by Histogram Classification |
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