DocumentCode
624663
Title
Fingerprint subclassification using rotation-invariant features
Author
Yong, A. ; Tiande Guo ; Yanping Wu ; Guangqi Shao
Author_Institution
Sch. of Math. Sci., Grad. Univ. of Chinese Acad. of Sci., Beijing, China
fYear
2013
fDate
9-11 June 2013
Firstpage
504
Lastpage
509
Abstract
A new method for fingerprint subclassification is proposed. First, a rotation-invariant feature is generated by rotation-invariant distance between orientation features. Then, fuzzy methods are adopted in both clustering step and classification step. With an introduced parameter, the balance between accuracy and average comparison times is made. The results show that the clustered subclasses are reasonable and the classification accuracy outperforms the combinations of crisp methods and fuzzy methods.
Keywords
feature extraction; fingerprint identification; fuzzy set theory; image classification; pattern clustering; classification accuracy; clustered subclasses; clustering step; fingerprint subclassification; fuzzy method; orientation feature; rotation-invariant distance; rotation-invariant feature; Accuracy; Clustering algorithms; Databases; Educational institutions; Fingerprint recognition; Roads; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4673-6248-1
Type
conf
DOI
10.1109/ICICIP.2013.6568127
Filename
6568127
Link To Document