Detection of individual specimens in populations using contour energies
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Contour energy features for recognition of biological specimens in population images
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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In this paper, we present a method to combine a grammatical model that encodes a priori shape information with the ziplock snakes presented by Neuenschwander et al. (1997). A competing mechanism is adopted to take advantage of the shape models without inducing excessive computation. The resulting model-based ziplock snakes have many advantages over the original model: they can accurately locate contour features, produce more refined results, and deal with multiple contours, missing image cues, and noise.