Abstract
Image classification is very helpful for organizing large image data-bases and content based image retrieval (CBIR). However, it is very complex and challenging because of lacking effective methods. In this paper, we present a tree representation of images based on rectangular-shape partition. Then an adaptive processing algorithm is adopted to perform the classification task. Experimental results on seven categories of scenery images show that the structural representations are better than the traditional methods and our previous work based on quadtree representation of fixed partition.
| Original language | English |
|---|---|
| Pages (from-to) | 274-280 |
| Number of pages | 7 |
| Journal | Lecture Notes in Computer Science |
| Volume | 3497 |
| Issue number | II |
| Publication status | Published - 26 Sept 2005 |
| Event | Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China Duration: 30 May 2005 → 1 Jun 2005 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science