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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing: PIKS Inside
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
A hybrid boundary detection algorithm based on watershed and snake
Pattern Recognition Letters
Seeded region growing: an extensive and comparative study
Pattern Recognition Letters
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ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Lip image segmentation using fuzzy clustering incorporating an elliptic shape function
IEEE Transactions on Image Processing
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The study of biology and population dynamics of fish species requires the routine estimation of fecundity in individual fish in many fisheries laboratories. The traditional procedure used by fisheries research is to count the oocytes manually on a subsample of known weight of the ovary, and to measure few oocytes under a binocular microscope. This process can be done on a computer using an interactive tool to count and measure oocytes. In both cases, the task is very time consuming, which implies that fecundity studies are rarely conducted routinely. We attempt to design an algorithm being able to extract the oocytes in a histological image. In a previous work [1], a statistical comparison of the performance of region and edge segmentation approaches was presented. The results have been encouraging but the edge based approach needed to mark manually the centers of the cells of interest. This paper proposes a non-guided method to extract the cells of interest based on edge information. In a post-processing stage, the segmentation results of the region and edge approaches are combined to improve the performance. The rate of oocyte detection has been increased to 82% when the demanded overlap between machine detection and true oocyte area is greater than 75%.