IMAGE SEGMENTATION Segmentation of an image entails the division or separation of the image into regions of similar attribute. The most basic attribute for segmentation is image luminance amplitude for a monochrome image and color components for a color image. Image edges and texture are also useful attributes for segmentation. The definition of segmentation adopted in this chapter is deliberately restrictive; no contextual information is utilized in the segmentation. Furthermore, segmentation does not involve classifying each segment | Digital Image Processing PIKS Inside Third Edition. William K. Pratt Copyright 2001 John Wiley Sons Inc. ISBNs 0-471-37407-5 Hardback 0-471-22132-5 Electronic 17 IMAGE SEGMENTATION Segmentation of an image entails the division or separation of the image into regions of similar attribute. The most basic attribute for segmentation is image luminance amplitude for a monochrome image and color components for a color image. Image edges and texture are also useful attributes for segmentation. The definition of segmentation adopted in this chapter is deliberately restrictive no contextual information is utilized in the segmentation. Furthermore. segmentation does not involve classifying each segment. The segmenter only subdivides an image it does not attempt to recognize the individual segments or their relationships to one another. There is no theory of image segmentation. As a consequence. no single standard method of image segmentation has emerged. Rather. there are a collection of ad hoc methods that have received some degree of popularity. Because the methods are ad hoc. it would be useful to have some means of assessing their performance. Haralick and Shapiro 1 have established the following qualitative guideline for a good image segmentation Regions of an image segmentation should be uniform and homogeneous with respect to some characteristic such as gray tone or texture. Region interiors should be simple and without many small holes. Adjacent regions of a segmentation should have significantly different values with respect to the characteristic on which they are uniform. Boundaries of each segment should be simple. not ragged. and must be spatially accurate. Unfortunately. no quantitative image segmentation performance metric has been developed. Several generic methods of image segmentation are described in the following sections. Because of their complexity. it is not feasible to describe all the details of the various algorithms. Surveys of image segmentation .
