International Journal of Computer Vision
A Minimum Cost Approach for Segmenting Networks of Lines
International Journal of Computer Vision
Vessel Extractio Techniques and Algorithms: A Survey
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Shape-Based Recognition of Wiry Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computerized cell image analysis: past, present, and future
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Guiding ziplock snakes with a priori information
IEEE Transactions on Image Processing
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
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In this paper we present an approach to perform automated analysis of nematodes in population images. Occlusion, shape variability and structural noise make reliable recognition of individuals a task difficult. Our approach relies on shape and geometrical statistical data obtained from samples of segmented lines. We study how shape similarity in the objects of interest, is encoded in active contour energy component values and exploit them to define shape features. Without having to build a specific model or making explicit assumptions on the interaction of overlapping objects, our results show that a considerable number of individual can be extracted even in highly cluttered regions when shape information is consistent with the patterns found in a given sample set.