A neighbor-finding algorithm involving the application of SNAM in binary-image representation

1Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

In view of the low execution efficiency and poor practicability of the existing neighbor-finding method, a fast neighbor-finding algorithm is put forward on the basis of Square Non-symmetry and Antipacking Model (SNAM) for binary-image. First of all, the improved minor-diagonal scanning way is applied to strengthen SNAM's adaptability to various textures, thus reducing the total number of nodes after coding; then the storage structures for its sub-patterns are standardized and a grid array is used to recover the spatial-position relationships among sub-patterns, so as to further reduce the complexity of the neighbor-finding algorithm. Experimental result shows that this method's execution efficiency is significantly higher than that of the classic Linear Quad Tree (LQT)-based neighbor-finding method.

Cite

CITATION STYLE

APA

He, J., Guo, H., & Hu, D. (2015). A neighbor-finding algorithm involving the application of SNAM in binary-image representation. Telkomnika (Telecommunication Computing Electronics and Control), 13(4), 1319–1329. https://doi.org/10.12928/TELKOMNIKA.v13i4.1899

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free