Path: Top -> Journal -> Telkomnika -> 2015 -> Vol 13, No 4: December
A Neighbor-finding Algorithm Involving the Application of SNAM in Binary-image Representation
A Neighbor-finding Algorithm Involving the Application of SNAM in Binary-image Representation
Journal from gdlhub / 2016-11-16 06:30:51By : Jie He, Hui Guo, Defa Hu, Telkomnika
Created : 2015-12-01, with 1 files
Keyword : Neighbor-Finding; SNAM for Binary-Image; Minor-Diagonal Scanning Mode; Grid Array
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/1899
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 SNAMs 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 methods execution efficiency is significantly higher than that of the classic Linear Quad Tree (LQT)-based neighbor-finding method.
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 SNAMs 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 methods execution efficiency is significantly higher than that of the classic Linear Quad Tree (LQT)-based neighbor-finding method.
Property | Value |
---|---|
Publisher ID | gdlhub |
Organization | Telkomnika |
Contact Name | Herti Yani, S.Kom |
Address | Jln. Jenderal Sudirman |
City | Jambi |
Region | Jambi |
Country | Indonesia |
Phone | 0741-35095 |
Fax | 0741-35093 |
Administrator E-mail | elibrarystikom@gmail.com |
CKO E-mail | elibrarystikom@gmail.com |
Print ...
Contributor...
- , Editor: sukadi
Downnload...
Download for member only.
1899-6168-1-PB
File : 1899-6168-1-PB.pdf
(238847 bytes)