A Markovian model for contour grouping

摘要

Classical methods of contour extraction do not always allow the detection of all the contours. For instance, the contours obtained by a Canny-Deriche filter have some gaps, especially at corners or at T-junctions. In this paper, we present an algorithm which restores incomplete contours. We model the image by a Markov Random Field. In order to complete the contours, several criteria are defined and introduced in an energy function, which has to be optimized. The deterministic ICM (“Iterated Conditional Mode”) relaxation algorithm is implemented to minimize this energy function. The result is a contour image consisting of closed contours. This method has been tested on different images which present different types of difficulties [indoors, outdoors, satellite (SPOT), industrial and medical images].