The Flat Zone Approach and Color Images

Abstract

This paper treats the application of the flat zone approach for color images. For gray-level images, the flat zone approach was presented in (Crespo & Serra 1993) as a segmentation approach that imposes an inclusion relationship between the flat zones (or piecewise-constant regions) of the input image and the regions of the output partition. That is, a flat zone segmentation method behaves like a connected operator. Color images are formed by several (a priori) independent bands. In this paper we discuss how color images need a different treatment from that used for gray-level images. For gray-level images, the flat zone inclusion relationship preserves the shapes of the features that are observed in the input. On the other hand, for color images this desirable shape-preservation effect would not be obtained by forcing the inclusion relationship between the flat zones of each band and the regions of the output partition. A mask that contains the important regions of the color image, computed for each color band, is employed to restrict the flat zone inclusion relationship to those flat zones belonging to the mask. As in the gray-level case, the presented color segmentation method uses a hierarchical waiting queue algorithm that makes it computationally efficient.

Formerly at the School of Electrical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA