Thresholding Image Segmentation Based on the Volume Analysis of Spatial Regions

Abstract

In the first part of the paper a new theoretical approach to the problem of image segmentation is described. A method for automatic segmenting of an unknown number and unknown location of objects in an image has been proposed. This method is based on both local properties of neighbouring pixels and global image features. To allow for automated segmentation, slices are formed at different values of the threshold level, which contain spatial uniformity regions. In the second part, the image segmentation is considered as a problem of selection of slices, which should comprise regions with features satisfying the requirements desired. The selection is based on the proposed minima criterion including a volume analysis of neighbouring slices. An important characteristic of the approach is that it reflects object shapes devoid of noise, and does not use heuristic parameters such as an edge value. The results of this method are presented on several examples containing greyscale images of objects of different brightness.