Name
Abstract | ||
|---|---|---|
The Interpolation-Based Bintree (IBB) is a new encoding scheme for representing binary images and is storage-saving. In the IBB only the black leaves are saved, called bincodes, as the compressed codes for the image. In this paper a fast neighbor finding algorithm is presented on bincodes. Given a sequence of bincodes with size n, our algorithm is performed in O((lmax −lmin+ 1) × n) time with the same memory complexity, where lmax and lmin are the maximal level and the minimal level, respectively, at which the given bincodes reside. Our algorithm is faster than the previous one [C.-Y. Huang and K.-L. Chung, Pattern Recognition 28(3),409–420 (1995)]. Experimental results for a practical version are included. The experimental values confirm our theoretical results. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/0031-3203(96)00167-7 | Pattern Recognition |
Keywords | Field | DocType |
Bincode,Interpolation-based bintree,Linear bintree,Neighbor finding,Complexity analysis | Neighbor finding,Binary image,Interpolation,Binary tree,Image processing,Algorithm,Data compression,Time complexity,Mathematics,Encoding (memory) | Journal |
Volume | Issue | ISSN |
29 | 9 | 0031-3203 |
Citations | PageRank | References |
6 | 0.50 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chi-Yen Huang | 1 | 216 | 12.02 |
| Kuo-Liang Chung | 2 | 1166 | 121.24 |