Name
Abstract | ||
|---|---|---|
This paper introduces a new feature vector for shape-based image indexing and retrieval. This feature classifies image edges based on two factors: their orientations and correlation between neighboring edges. Hence it includes information of continuous edges and lines of images and describes major shape properties of images. This scheme is effective and robustly tolerates translation, scaling, color, illumination, and viewing position variations. Experimental results show superiority of proposed scheme over several other indexing methods. Averages of precision and recall rates of this new indexing scheme for retrieval as compared with traditional color histogram are 1.99 and 1.59 times, respectively. These ratios are 1.26 and 1.04 compared to edge direction histogram. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0031-3203(03)00010-4 | Pattern Recognition |
Keywords | Field | DocType |
Image retrieval,Image indexing,Shape-based indexing,Non-segmentation based indexing | Computer vision,Histogram,Feature vector,Color histogram,Pattern recognition,Precision and recall,Search engine indexing,Image retrieval,Correlation,Artificial intelligence,Scaling,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 8 | 0031-3203 |
Citations | PageRank | References |
70 | 2.48 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fariborz Mahmoudi | 1 | 138 | 11.66 |
| Jamshid Shanbehzadeh | 2 | 253 | 15.43 |
| Amir-Masoud Eftekhari-Moghadam | 3 | 135 | 9.87 |
| Hamid Soltanian-Zadeh | 4 | 613 | 84.11 |