Abstract
In this paper, inspired by the optimization idea of the packing problem, we propose an improved indirect triangle non-symmetry and anti-packing model (IITNAM) for gray image representation. Also, we present an algorithm of the IITNAM for gray images and analyze the total data amount of the algorithm. By comparing the representation algorithm of the IITNAM with those of the latest indirect triangle non-symmetry and anti-packing model (ITNAM) and the popular linear quadtree (LQT), the theoretical and experimental results show that the former can greatly reduce the numbers of subpatterns or nodes and simultaneously save the data storage much more effectively than the latter, and therefore it is a better method to represent gray images. The representation method of the IITNAM shows a very strong promise, and it is valuable for the further theoretical research and potential business foreground, such as reducing storage space, increasing transmission speed, and improving pattern match efficiency.
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