Name
Abstract | ||
|---|---|---|
In a process of insect footprint recognition, footprint segments need to be extracted from scanned insect footprints in order to find out appropriate features for classification. In this paper, we use a clustering method in a preprocessing stage for extraction of insect footprint segments. In general, sizes and strides of footprints may be different according to type and size of an insect for recognition. Therefore we propose a method for insect footprint segment extraction using an improved ART2 algorithm regardless of size and stride of footprint pattern. In the improved ART2 algorithm, an initial threshold value for clustering is determined automatically using the contour shape of the graph created by accumulating distances between all the spots within a binarized footprint pattern image. In the experimental results, applying the proposed method to two kinds of insect footprint patterns, we illustrate that clustering is accomplished correctly. |
Year | Venue | Keywords |
|---|---|---|
2007 | PSIVT | scanned insect footprint,insect footprint segment extraction,insect footprint segment,footprint pattern,binarized footprint pattern image,art2 algorithm,threshold selection,insect footprint pattern,insect footprint recognition,clustering method,footprint segment,clustering |
Field | DocType | Volume |
Computer vision,Graph,Pattern recognition,Segmentation,Computer science,Preprocessor,Artificial intelligence,Footprint,Cluster analysis | Conference | 4872 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-77128-X | 2 |
PageRank | References | Authors |
0.39 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bok-Suk Shin | 1 | 68 | 9.27 |
| Eui-Young Cha | 2 | 49 | 11.24 |
| Young Woon Woo | 3 | 31 | 8.39 |
| Reinhard Klette | 4 | 1743 | 228.94 |