A Compressed Representation of Mid-Crack Code with Huffman Code

Abstract

Contour representation of binary object is increasingly used in image processing and pattern recognition. Chain code and crack code are popular methods of contour encoding. However, by using these methods, an accurate estimate of geometric features like area and perimeter of objects are difficult to obtain. Mid- crack code, another contour encoding method, can help to obtain more accurate estimate of the geometric features of objects. Though a considerable amount of reduction of the size of images is obtained by fixed-length mid-crack code, yet, more efficient encoding is possible by considering and applying variable-length encoding technique. In this paper, a compressed mid-crack code is proposed based on the Huffman code. Experiments performed on different images yield that the proposed representation reduces the number of bits require to encode the contour of an image with compared to the classical mid-crack code.