A fast algorithm for computing moments of gray images based on NAM and extended shading approach

Authors:
Yunping Zheng;Mudar Sarem
Affiliations:
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China 510006;School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China 430074
Venue:
Frontiers of Computer Science in China
Year:
2011

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Abstract

Computing moments on images is very important in the fields of image processing and pattern recognition. The non-symmetry and anti-packing model (NAM) is a general pattern representation model that has been developed to help design some efficient image representation methods. In this paper, inspired by the idea of computing moments based on the S-Tree coding (STC) representation and by using the NAM and extended shading (NAMES) approach, we propose a fast algorithm for computing lower order moments based on the NAMES representation, which takes O(N) time where N is the number of NAM blocks. By taking three idiomatic standard gray images `Lena', `F16', and `Peppers' in the field of image processing as typical test objects, and by comparing our proposed algorithm with the conventional algorithm and the popular STC representation algorithm for computing the lower order moments, the theoretical and experimental results presented in this paper show that the average execution time improvement ratios of the proposed NAMES approach over the STC approach, and also the conventional approach are 26.63%, and 82.57% respectively while maintaining the image quality.