A New Perception-Based Segmentation Approach Using Combinatorial Pyramids

摘要

This paper presents a bottom-up approach for perceptual segmentation of natural images. The segmentation algorithm consists of two consecutive stages: firstly, the input image is partitioned into a set of blobs of uniform colour (pre-segmentation stage) and then, using a more complex distance which integrates edge and region descriptors, these blobs are hierarchically merged (perceptual grouping). Both stages are addressed using the Combinatorial Pyramid, a hierarchical structure which can correctly encode relationships among image regions at upper levels. Thus, unlike other methods, the topology of the image is preserved. The performance of the proposed approach has been initially evaluated with respect to groundtruth segmentation data using the Berkeley Segmentation Dataset and Benchmark. Although additional descriptors must be added to deal with textured surfaces, experimental results reveal that the proposed perceptual grouping provides satisfactory scores.