Name
Abstract | ||
|---|---|---|
The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide companies an automatic and reliable method to perform this task. In this paper a new method which uses texture descriptors based on the Curvelet Transform is proposed. Its performance has been compared with other texture descriptors based on the Wavelet transform, and also with moments based descriptors, as they seem to be successful for this problem. Texture descriptors performed better, and curvelet-based ones achieved the best hit rate (97%) and area under the ROC curve (0.99). |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-31298-4_53 | ICIAR (2) |
Keywords | Field | DocType |
veterinary field,best hit rate,curvelet-based texture description,important task,damaged boar spermatozoon,reliable method,roc curve,curvelet transform,acrosome status,boar sperm head image,new method,curvelet,classification,feature extraction | Hit rate,Computer vision,Curvelet transform,Pattern recognition,Computer science,Feature extraction,Sperm Head,Artificial intelligence,Area under the roc curve,Wavelet transform,Curvelet | Conference |
Volume | ISSN | Citations |
7325 | 0302-9743 | 6 |
PageRank | References | Authors |
0.51 | 10 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Víctor González-Castro | 1 | 90 | 10.70 |
| Enrique Alegre | 2 | 139 | 21.84 |
| Oscar García-Olalla | 3 | 42 | 4.24 |
| Diego García-Ordás | 4 | 14 | 1.64 |
| María Teresa García-Ordás | 5 | 37 | 4.45 |
| Laura Fernández-Robles | 6 | 54 | 12.95 |