A multilayer self-organizing feature map for range image segmentation

Abstract

This paper proposes and describes a hierarchical self-organizing neural network for range image segmentation. The multilayer self-organizing feature map (MLSOFM), which is an extension of the traditional (single-layer) self-organizing feature map (SOFM) is seen to alleviate the shortcomings of the latter in the context of range image segmentation. The problem of range image segmentation is formulated as one of vector quantization and is mapped onto the MLSOFM. The MLSOFM combines the ideas of self-organization and topographic mapping with those of multiscale image segmentation. Experimental results using real range images are presented.