A Neighbor-finding Algorithm Involving the Application of SNAM in Binary-Image Representation
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 Anti-packing 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.
Author: Jie He, Hui Guo, Defa
Hu
Journal Code: jptkomputergg150142
