Contour Extraction and Compression-Selected Topics

Abstract

The subject of this chapter is to describe selected topics on contour extraction, approximation and compression in spatial domain. Contours are treated as important image structure required in many applications, for example in analysis of medical image, computer vision, robot guidance, pattern recognition etc. Contour compression plays important role in many practical tasks associated with contour and image processing. The main approach solving the problem of contour compression is based on polygonal approximation. In this chapter the traditional and new methods for contour approximation in spatial domain are presented. These methods are often much faster than the methods of compression based on transform coding. In order to extract the contours from the image some algorithms have been developed. The selected well known methods for contour extraction and edge detection as well as the new algorithms are also presented in this chapter. The author is grateful to his Ph.D. students A. Ukasha and B. Fituri for their contribution in preparation of this chapter. 1. Contour Analysis and Extraction Contours and line drawings have been an important area in image data processing. In many applications, e.g., weather maps and geometric shapes, it is necessary to store and transmit large amounts of contours and line drawings and process the information by computers. Several approaches have been used to extract and encode the boundary points of contours and line drawings. The extracted data is then used for further processing and applications. Contour approximation and compression are some of the processing operations performed on contours and has been considered by several authors. In encoding contours and line drawings, efficient data compression and good reconstruction are both usually required. Freeman proposed an eight-directi onal encoding scheme for contour lines. The proposed chain code is obtained by superimposing a rectangular grid on the curve and then quantizing the curve to the nearest one of the eight possible grid points. The chain encoding scheme represents contour lines by 3 bits/link, where a link is defined as one of the eight possible straight-line segments between two adjacent quantized points. Efforts have been made to improve the coding efficiency. Freeman proposed a chain difference coding scheme which assigned variable-length codewords to the difference between two consecutive links. This coding scheme represents contour lines by about 2 to 2.1 bits/link on average.