Name
Abstract | ||
|---|---|---|
This paper presents a classification method of fingerprint using orientation field and support vector machines. It estimates orientation field through pixel gradient, then calculates the percentages of the directional block classes. These percentages are combined as a four dimensional vector, by which the trained hierarchical classifier classifies the fingerprint into one of the six classes it belongs to. Experiments show that this method has high classification accuracy as well as low computational time cost. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICNC.2007.700 | ICNC |
Keywords | Field | DocType |
orientation field,support vector machine,svm-based fingerprint classification,directional block class,classification method,trained hierarchical classifier,low computational time cost,pixel gradient,dimensional vector,high classification accuracy,image classification,fingerprint identification,support vector machines | Structured support vector machine,Computer vision,Pattern recognition,Computer science,Support vector machine,Fingerprint,Pixel,Artificial intelligence,Relevance vector machine,Hierarchical classifier,Contextual image classification,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2875-9 | 4 | 0.50 |
References | Authors | |
4 | 2 | |