Constraint K-Segment Principal Curves

Author(s):  
Junping Zhang ◽  
Dewang Chen
Keyword(s):  
Author(s):  
Danton Diego Ferreira ◽  
Jose Manoel de Seixas ◽  
Carlos Augusto Duque ◽  
Augusto S. Cerqueira ◽  
Paulo Fernando Ribeiro

Author(s):  
HONGYUN ZHANG ◽  
DUOQIAN MIAO ◽  
CAIMING ZHONG

It is difficult but crucial for minutiae extraction and pseudo minutiae deletion of low quality fingerprint images in auto fingerprint identification systems. Traditional methods based on thinning images or gray-level images are, however, susceptible to noise. Reference 14 indicated that principal curves based fingerprint minutiae extraction was feasible to overcome the drawback, but the extended polygonal line (EPL) principal curves algorithm used in the paper extracted the principal curves ineffectively. As the fingerprint data sets are usually large, the original EPL principal curves algorithm is time-consuming. Meanwhile, scattered fingerprint data lead to the deviation of fingerprint skeleton. In this paper, the algorithm is modified, and a fingerprint minutiae extraction and pseudo minutiae detection method based on principal curves is proposed. Experimental results show that the modified EPL principal curves algorithm outperforms the original EPL algorithm both in efficiency and quality, and the proposed minutiae extraction method outperforms the methods proposed by Miao under noise conditions.


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