On the optimal detection of curves in noisy pictures
Communications of the ACM
Computer Vision
Dynamic Programming
Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational strategies for object recognition
ACM Computing Surveys (CSUR)
Encoding of a priori Information in Active Contour Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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Dynamic programming was applied to locate the glomeruli in microscopic images of kidney tissue section. The glomeruli were modeled by a polygon whose sides could be varied within a given range of lengths. The objects were located by determining the best match of the model according to a so-called optimum criterion in which all possible shapes were evaluated at all possible positions in the input image. The best model was selected according to the maximum average gray level. To increase the probability of obtaining a closed contour, a distance criterion was added and the maximum gray-level requirement was relaxed somewhat. The optimum criterion was modified to include a directionality constraint in which the difference in angle between model segments and the edge values in the image was minimized, thereby increasing the performance of the method. A hierarchical multiresolution strategy was used to reduce calculation time. The cyclical property of a contour is also taken into account.