Name
Abstract | ||
|---|---|---|
Skeleton is a very important feature for shape-based image classification. In this paper, we apply the discrete shock graph-based skeleton features to classify shapes into predefined groups, using a k-means clustering algorithm. The graph edit cost obtained by transforming database image graph into the respected query graph, will be used as distance function for the k-means clustering. To verify the performance of the suggested algorithm, we tested it on MPEG-7 dataset and our algorithm shows excellent performance for shape classification. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-17604-3_29 | COMMUNICATION AND NETWORKING, PT II |
Keywords | Field | DocType |
Medial axis, shock graph, edit distance, k-means clustering | Edit distance,Graph,k-means clustering,Pattern recognition,Computer science,Metric (mathematics),Jaro–Winkler distance,Algorithm,Medial axis,Artificial intelligence,Cluster analysis,Contextual image classification | Conference |
Volume | ISSN | Citations |
120 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Solima Khanam | 1 | 4 | 1.58 |
| Seok-Woo Jang | 2 | 55 | 12.72 |
| Woojin Paik | 3 | 89 | 22.44 |