Abstract
A novel feature matrix similarity measure method, which is suitable for two dimensional object recognition and matching, is presented. In this method, a similar-row vector is produced by comparing dynamic programming (DP) matching distances, which describe the similarity between the row of a query matrix and that of a sample matrix. And the similar-row vector is used to represent the query matrix. Then the DP matching is again performed to obtain a similarity measure. The proposed method is employed in an image retrieval system using a dominant color feature matrix representation. The experimental results show that the method is efficient.
| Original language | English |
|---|---|
| Pages (from-to) | 497-502 |
| Number of pages | 6 |
| Journal | Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence |
| Volume | 19 |
| Issue number | 4 |
| State | Published - Aug 2006 |
Keywords
- Dynamic programming matching
- Feature matrix
- Image retrieval
- Similarity measure