Detection of individual specimens in populations using contour energies

Authors:
Daniel Ochoa;Sidharta Gautama;Boris Vintimilla
Affiliations:
Department of telecommunication and information processing, Ghent University, Ghent, Belgium and Centro de Vision y Robotica, Facultad de Ingenieria en Electricidad y Computación, ESPOL Unive ...;Department of telecommunication and information processing, Ghent University, Ghent, Belgium;Centro de Vision y Robotica, Facultad de Ingenieria en Electricidad y Computación, ESPOL University, Guayaquil, Ecuador
Venue:
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Year:
2007

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Abstract

In 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.