Abstract
Active Contours constitute a widely used Pattern Recognition technique. Classical active contours are based on different methodologies. This paper reviews the algorithm paradigms most frequently utilized in active contours (variational calculus, dynamic programming and greedy algorithm) in a practical application, comparing chemical data with computer vision results. An experiment has been designed to recognize muscles from Magnetic Resonance (MR) images of Iberian ham at different maturation stages in order to calculate their volume change, using different active contour approaches. Our main findings can be summarized as two: The feasible application of active contours to recognize muscles in MR images, and the early way to automate the ripening process for Iberian ham.
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