Fingerprint Classification Based on Continuous Orientation Field and Singular Points
Fingerprint classification is crucial to reduce the processing time in a large-scale database. In this paper a fingerprint classification based on continuous orientation field and singular points is proposed. The continuous orientation field can not only filter the noises in point directional image,but also represent the basic structural feature of fingerprint more precisely.Singularities are the most important and reliable feature in classification.The reliable and fast classification algorithm is made possible by a simple but effective combination of continuous orientation field and the modified Poincare index in the determination of singular points.The experiment results show the effectiveness of the proposed method in producing good classification result.
Fingerprint classification Singular points Continuous orientation field
Xiuyou Wang Feng Wang Jianzhong Fan Jiwen Wang
School of Computer and Information Fu yang Normal College Fu yang,China School of Computer Science and Technology AnHui University Heifei,China
国际会议
上海
英文
2718-2722
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）