Plankton Detection and Tracking Using Frequency Filtering
Sophisticated optical hardware allows performing computationally heavy image processing with the speed of light, before the actual frame is captured by a camera sensor. Filtering in the frequency plane of the optical system can be used for fast pattern detection, which constitutes one of the major p...
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| creator | Matuszewski, Damian J. Lopes, Rubens M. |
| description | Sophisticated optical hardware allows performing computationally heavy image processing with the speed of light, before the actual frame is captured by a camera sensor. Filtering in the frequency plane of the optical system can be used for fast pattern detection, which constitutes one of the major problems in plankton image processing. The aim of the research presented in this paper was to design a set of spatial filters allowing for particles detection and tracking in video streams. The method enables in a limited scope to distinguish the species of the tracked organisms. This initial recognition is based on the size differences. |
| doi_str_mv | 10.1109/NAVCOMP.2013.20 |
| format | Conference Proceeding |
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Filtering in the frequency plane of the optical system can be used for fast pattern detection, which constitutes one of the major problems in plankton image processing. The aim of the research presented in this paper was to design a set of spatial filters allowing for particles detection and tracking in video streams. The method enables in a limited scope to distinguish the species of the tracked organisms. 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Filtering in the frequency plane of the optical system can be used for fast pattern detection, which constitutes one of the major problems in plankton image processing. The aim of the research presented in this paper was to design a set of spatial filters allowing for particles detection and tracking in video streams. The method enables in a limited scope to distinguish the species of the tracked organisms. This initial recognition is based on the size differences.</description><subject>Biomedical optical imaging</subject><subject>frequency filtering</subject><subject>Frequency-domain analysis</subject><subject>Holography</subject><subject>Optical filters</subject><subject>Optical imaging</subject><subject>Optical sensors</subject><subject>optical systems</subject><subject>Organisms</subject><subject>pattern matching</subject><subject>plankton detection</subject><isbn>9780769551234</isbn><isbn>0769551238</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjLtOw0AQRZcCCRRcU9D4BxxmPN7HlJHBASmQFAlttKzHaIkxYJsif48jaM65OsVV6hphjgh8-7x4KddPm3kOSBPOVMLWgTWsNeZUXKhkGN4BANlMmS4Vb1rfHcbPLr2TUcIYp-W7Ot32Phxi95buhhOrXr5_pAvHtIrtKP3UrtR549tBkn_P1K6635YP2Wq9fCwXqyyi1WPGlmyQHNkikTc1OaOhcL5g8dIAUaONbzybV6cdQlEjBpBQNAYFmZlm6ubvN4rI_quPH74_7o1xBtHRL9UKRM8</recordid><startdate>201303</startdate><enddate>201303</enddate><creator>Matuszewski, Damian J.</creator><creator>Lopes, Rubens M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201303</creationdate><title>Plankton Detection and Tracking Using Frequency Filtering</title><author>Matuszewski, Damian J. ; Lopes, Rubens M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-9737ce2197133a6d3865048a49eaef033f56afa96b858104d11c0ec4f61e19993</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Biomedical optical imaging</topic><topic>frequency filtering</topic><topic>Frequency-domain analysis</topic><topic>Holography</topic><topic>Optical filters</topic><topic>Optical imaging</topic><topic>Optical sensors</topic><topic>optical systems</topic><topic>Organisms</topic><topic>pattern matching</topic><topic>plankton detection</topic><toplevel>online_resources</toplevel><creatorcontrib>Matuszewski, Damian J.</creatorcontrib><creatorcontrib>Lopes, Rubens 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 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>Matuszewski, Damian J.</au><au>Lopes, Rubens M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Plankton Detection and Tracking Using Frequency Filtering</atitle><btitle>2013 Symposium on Computing and Automation for Offshore Shipbuilding</btitle><stitle>navcomp</stitle><date>2013-03</date><risdate>2013</risdate><spage>75</spage><epage>80</epage><pages>75-80</pages><eisbn>9780769551234</eisbn><eisbn>0769551238</eisbn><coden>IEEPAD</coden><abstract>Sophisticated optical hardware allows performing computationally heavy image processing with the speed of light, before the actual frame is captured by a camera sensor. Filtering in the frequency plane of the optical system can be used for fast pattern detection, which constitutes one of the major problems in plankton image processing. The aim of the research presented in this paper was to design a set of spatial filters allowing for particles detection and tracking in video streams. The method enables in a limited scope to distinguish the species of the tracked organisms. This initial recognition is based on the size differences.</abstract><pub>IEEE</pub><doi>10.1109/NAVCOMP.2013.20</doi><tpages>6</tpages></addata></record> |
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| ispartof | 2013 Symposium on Computing and Automation for Offshore Shipbuilding, 2013, p.75-80 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical optical imaging frequency filtering Frequency-domain analysis Holography Optical filters Optical imaging Optical sensors optical systems Organisms pattern matching plankton detection |
| title | Plankton Detection and Tracking Using Frequency Filtering |
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