Hierarchical image sequence model for segmentation: application to region-based sequence coding
Ferran Marqués, Victor Vera, Antoni Gasull Llampallas · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
This paper studies the performance of an image sequence model based on Compound Random Fields when used for segmentation purposes. The fact of using a hierarchical model allows characterizing separately the texture and contour information within the sequence. Moreover, temporal and spatial contour behavior can also be described independently. This separated characterization allows to impose constraints on the kind of contours to be obtained and to introduce some a priori knowledge in the segmentation procedure. The way to exploit these features for an object-based sequence coding scheme is analyzed. The influence of the model parameters on the segmentation results is analyzed, in order to achieve segmentations which can be easily coded. The main sought characteristics are smooth spatial contours, slow temporal variations and homogeneous textures. Two different segmentation algorithms are used for this analysis, a recursive and a nonrecursive one.