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MORPHOLOGICAL IMAGE PROCESSING Morphological image processing is a type of processing in which the spatial form or structure of objects within an image are modified. Dilation, erosion, and skeletonization are three fundamental morphological operations. With dilation, an object grows uniformly in spatial extent, whereas with erosion an object shrinks uniformly. Skeletonization results in a stick figure representation of an object. | 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 14 MORPHOLOGICAL IMAGE PROCESSING Morphological image processing is a type of processing in which the spatial form or structure of objects within an image are modified. Dilation erosion and skeletonization are three fundamental morphological operations. With an object grows uniformly in spatial extent whereas with erosion an object shrinks uniformly. Skeletonization results in a stick figure representation of an object. The basic concepts of morphological image processing trace back to the research on spatial set algebra by Minkowski 1 and the studies of Matheron 2 on topology. Serra 3-5 developed much of the early foundation of the subject. Steinberg 6 7 was a pioneer in applying morphological methods to medical and industrial vision applications. This research work led to the development of the cytocomputer for high-speed morphological image processing 8 9 . In the following sections morphological techniques are first described for binary images. Then these morphological concepts are extended to gray scale images. . BINARY IMAGE CONNECTIVITY Binary image morphological operations are based on the geometrical relationship or connectivity of pixels that are deemed to be of the same class 10 11 . In the binary image of Figure the ring of black pixels by all reasonable definitions of connectivity divides the image into three segments the white pixels exterior to the ring the white pixels interior to the ring and the black pixels of the ring itself. The pixels within each segment are said to be connected to one another. This concept of connectivity is easily understood for Figure but ambiguity arises when considering Figure . Do the black pixels still define a ring or do they instead form four disconnected lines The answers to these questions depend on the definition of .