Integer Gaussian convolution with cache memory for real-time processing of the Scale Invariant Feature Transform algorithm
The Gaussian smoothing operator is a 2-D convolution operator which is used to blur images and remove detail and noise in the SIFT (scale invariant feature transform) algorithm. For real-time processing of SIFT, we use our integer Gaussian filtering and cache memory managing schemes using SSE instru...
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| creator | Le Tran Su Phil Jung Ghang Jong Soo Lee |
| description | The Gaussian smoothing operator is a 2-D convolution operator which is used to blur images and remove detail and noise in the SIFT (scale invariant feature transform) algorithm. For real-time processing of SIFT, we use our integer Gaussian filtering and cache memory managing schemes using SSE instructions. Single instruction multiple data (SIMD) extensions are currently available in new Pentium processors. We optimize the integer Gaussian filter mask for better precision in key-points detection and compare the result of applying the scheme with those obtained by using the floating processing technique. We apply our scheme to various kinds of images and measure the effectiveness. |
| doi_str_mv | 10.1109/IFOST.2007.4798587 |
| format | Conference Proceeding |
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We apply our scheme to various kinds of images and measure the effectiveness.</description><subject>Cache memory</subject><subject>Convolution</subject><subject>Filtering</subject><subject>Filters</subject><subject>Gaussian filtering</subject><subject>Gaussian noise</subject><subject>Image converters</subject><subject>Information technology</subject><subject>integer Gaussian mask</subject><subject>Kernel</subject><subject>Shape</subject><subject>SIFT algorithm</subject><subject>Smoothing methods</subject><subject>SSE instructions</subject><isbn>9781424435890</isbn><isbn>1424435897</isbn><isbn>9781424418312</isbn><isbn>1424418313</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkMFqAjEYhFOK0Nb6Au0lL7A22U02ybFItQuCB-1Z_o3_aspuItlosU_fLRU6l2Fg5jsMIU-cTTln5qWar9abac6YmgpltNTqhkyM0lzkQnBd8Pz2PxdSGzYiD791w5Ti-R2Z9P0nGyRkoQW_J9-VT7jHSBdw6nsHntrgz6E9JRc8_XLpQC3YA9IOuxAvtAmRRoQ2S65DeozB4jDzexoamoba2kKLtPJniAMs0TlCOkWkmwi-H8YdhXYf4sDtHsmogbbHydXH5GP-tpm9Z8vVopq9LjPHlUyZRKMZWGPqupCQG8lqWzaa21KKsmG4EzUvSzC5RasasI1SuihzYxUKs2N1MSbPf1yHiNtjdB3Ey_Z6X_ED19pkHA</recordid><startdate>200710</startdate><enddate>200710</enddate><creator>Le Tran Su</creator><creator>Phil Jung Ghang</creator><creator>Jong Soo Lee</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200710</creationdate><title>Integer Gaussian convolution with cache memory for real-time processing of the Scale Invariant Feature Transform algorithm</title><author>Le Tran Su ; Phil Jung Ghang ; Jong Soo Lee</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-5e980ac99bb35a2950bc6f81c6546f0ed4b166a92cec7facf7783629c7e49d0b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Cache memory</topic><topic>Convolution</topic><topic>Filtering</topic><topic>Filters</topic><topic>Gaussian filtering</topic><topic>Gaussian noise</topic><topic>Image converters</topic><topic>Information technology</topic><topic>integer Gaussian mask</topic><topic>Kernel</topic><topic>Shape</topic><topic>SIFT algorithm</topic><topic>Smoothing methods</topic><topic>SSE instructions</topic><toplevel>online_resources</toplevel><creatorcontrib>Le Tran Su</creatorcontrib><creatorcontrib>Phil Jung Ghang</creatorcontrib><creatorcontrib>Jong Soo Lee</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>Le Tran Su</au><au>Phil Jung Ghang</au><au>Jong Soo Lee</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Integer Gaussian convolution with cache memory for real-time processing of the Scale Invariant Feature Transform algorithm</atitle><btitle>2007 International Forum on Strategic Technology</btitle><stitle>IFOST</stitle><date>2007-10</date><risdate>2007</risdate><spage>298</spage><epage>301</epage><pages>298-301</pages><isbn>9781424435890</isbn><isbn>1424435897</isbn><eisbn>9781424418312</eisbn><eisbn>1424418313</eisbn><abstract>The Gaussian smoothing operator is a 2-D convolution operator which is used to blur images and remove detail and noise in the SIFT (scale invariant feature transform) algorithm. For real-time processing of SIFT, we use our integer Gaussian filtering and cache memory managing schemes using SSE instructions. Single instruction multiple data (SIMD) extensions are currently available in new Pentium processors. We optimize the integer Gaussian filter mask for better precision in key-points detection and compare the result of applying the scheme with those obtained by using the floating processing technique. We apply our scheme to various kinds of images and measure the effectiveness.</abstract><pub>IEEE</pub><doi>10.1109/IFOST.2007.4798587</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2007 International Forum on Strategic Technology, 2007, p.298-301 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cache memory Convolution Filtering Filters Gaussian filtering Gaussian noise Image converters Information technology integer Gaussian mask Kernel Shape SIFT algorithm Smoothing methods SSE instructions |
| title | Integer Gaussian convolution with cache memory for real-time processing of the Scale Invariant Feature Transform algorithm |
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