Rectangle NAM Image Representation and Contour Extraction of Binary Image Represented by NAM

Less data and faster operation are the aims of image representation. The popular matrix image representation needs huge storage space and its processing speed is usually slow because of its operation pattern of pixel to pixel. Some traditional image representations with hiberarchy (e.g. quadtree) have operation pattern of block to block and can enhance some processing speed, but they can’t get the best segment of an image because of its symmetry. With the concept of packing problem, a non-symmetry anti-packing pattern representation model (NAM) is presented. NAM has less limitation when representing an image, so it can acquire higher compression ratio and do some image processing directly and more quickly. Comparison between rectangle NAM and other image representations proves that the rectangle NAM is an efficient representation at the aspect of data storage, and the experimental result of contour extraction of binary image represented by rectangle NAM proves that the rectangle NAM has the advantage of some image processing speed.