Analysis of relevant maxima in distance transform: an application to fast coarse image segmentation

Abstract

The Distance Transform is a powerful tool that has been used in many computer vision tasks. In this paper, the use of relevant maxima in distance transform's medial axis is proposed as a method for fast image data reduction. These disc-shaped maxima include morphological information from the object they belong to, and because maxima are located inside homogeneous regions, they also sum up chromatic information from the pixels they represent. Thus, maxima can be used instead of single pixels in algorithms which compute relations among pixels, effectively reducing computation times. As an example, a fast method for color image segmentation is proposed, which can also be used for textured zones detection. Comparisons with mean shift segmentation algorithm are shown.