Name
Abstract | ||
|---|---|---|
The notion of linear moment vector is introduced as an efficient approach for matching and normalization of affine deformed image. Least square error technique is introduced to improve the robustness and accuracy of the matching. By normalizing the linear moment vectors, the affine deformed image can be normalized. Our approaches are based only on regular moments that can be obtained easily from the image without extracting any feature point. The techniques can be generalized to n-dimensional case. The experiment results show that the proposed method gives good performance. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/j.patrec.2004.06.008 | Pattern Recognition Letters |
Keywords | Field | DocType |
efficient approach,linear moment vectors,feature point,regular moments,square error technique,normalization,good performance,experiment result,linear moment vector,regular moment,affine transformation,matching | Affine transformation,Affine shape adaptation,Normalization (statistics),Harris affine region detector,Artificial intelligence,Affine hull,Discrete mathematics,Affine combination,Pattern recognition,Affine coordinate system,Algorithm,Affine group,Mathematics | Journal |
Volume | Issue | ISSN |
25 | 14 | Pattern Recognition Letters |
Citations | PageRank | References |
1 | 0.36 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jin Liu | 1 | 316 | 50.24 |
| Tianxu Zhang | 2 | 206 | 23.18 |