Detection of individual specimens in populations using contour energies

dc.creatorOchoa, Daniel
dc.creatorGautama, Sidharta
dc.creatorVintimilla, Boris
dc.date2009-07-27
dc.date2009-07-27
dc.date2009-07-27
dc.date.accessioned2023-08-08T22:18:08Z
dc.date.available2023-08-08T22:18:08Z
dc.identifier978-3-540-74606-5
dc.identifierhttp://www.dspace.espol.edu.ec/handle/123456789/6143
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8089725
dc.descriptionIn this paper we study how shape information encoded in contour energy components values can be used for detection of microscopic organisms in population images. We proposed features based on shape and geometrical statistical data obtained from samples of optimized contour lines integrated in the framework of Bayesian inference for recognition of individual specimens. Compared with common geometric features the results show that patterns present in the image allow better detection of a considerable amount of individuals even in cluttered regions when sufficient shape information is retained. Therefore providing an alternative to building a specific shape model or imposing specific constrains on the interaction of overlapping objects.
dc.descriptionDepartment of telecommunication and information processing, Ghent University, St-Pieters Nieuwstraat 41, B-9000, Ghent, Belgium Centro de Vision y Robotica, Facultad de Ingenieria en Electricidad y Computación, ESPOL University, Km 30.5 via perimetral, 09015863, Guayaquil, Ecuador
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dc.languageen_US
dc.relationSpringer LNCS;4678
dc.rightsopenAccess
dc.subjectRECOGNITION
dc.subjectFEATURE EXTRACTION
dc.subjectSTATISTICAL SHAPE ANALYSIS
dc.titleDetection of individual specimens in populations using contour energies
dc.typeOther


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