Name
Abstract | ||
|---|---|---|
Aiming at the segmentation of low quality fingerprint images, a new framework, which is different from traditional methods that usually use some certain features to segment diversified images, is proposed. There are two contributions in this scheme: firstly, we introduce a quality estimation step before segmentation, which can remove a great many false traces effectively; secondly, a new feature eccentric moment is proposed to locate the blurry boundary. Then we segment the image using the new block feature of clarified image. Experimental results show that the proposed method can segment low quality fingerprint images properly. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICIG.2004.14 | ICIG |
Keywords | Field | DocType |
certain feature,fingerprint identification,feature eccentric moment,segment diversified image,low quality fingerprint image,image segmentation,new block feature,segment low quality fingerprint,quality estimation step,blurry boundary,eccentric moment,new framework,segmentation algorithm,new feature,diversified image segmentation,new segmentation algorithm | Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Fingerprint recognition,Image texture,Segmentation,Segmentation-based object categorization,Image segmentation,Fingerprint,Artificial intelligence,Biometrics | Conference |
ISBN | Citations | PageRank |
0-7695-2244-0 | 17 | 1.51 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongchao Shi | 1 | 24 | 5.65 |
| Yangsheng Wang | 2 | 750 | 66.25 |
| Jin Qi | 3 | 66 | 7.43 |
| Ke Xu | 4 | 23 | 3.85 |