Part Segmentation from 2D Edge Images by the MDL Criterion

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 ltering 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 are put in competition in a Minimum Description-Length (MDL) framework to select part hypotheses that most economically represent supporting edges in the \language" of generic parts.