Part segmentation from 2D edge images by the MDL criterion

Abstract In the context of part segmentation from 2D edge images, this paper presents some interesting results with a novel method that addresses the problem of filtering a redundant set of part hypotheses that retains only those that are likely to correspond to actual parts. In the proposed method, supporting evidence for hypotheses competes in a minimum description-length (MDL) framework to select part hypotheses that most economically represent supporting edges in the ‘language’ of generic parts.

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