Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fingerprint Smear Detection Based on Subband Feature Representation | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 412647 13 pages doi 2011 412647 Research Article Fingerprint Smear Detection Based on Subband Feature Representation Xiukun Yang College of Information and Communication Harbin Engineering University Harbin 150001 China Correspondence should be addressed to Xiukun Yang yangxiukun@ Received 5 July 2010 Revised 17 January 2011 Accepted 11 February 2011 Academic Editor A. Enis Cetin Copyright 2011 Xiukun Yang. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Fingerprint smear detection has become a challenging issue due to the erratic texture of the smear tissue and its similarity to normal finger area. This paper presents a novel fingerprint image smear detection approach integrating symmetric wavelet transform SWT gray level co-occurrence matrix and DCT. A feature extraction algorithm is first proposed by utilizing SWT to decompose each fingerprint and characterizing local texture features of defective finger tissue with the SWT coefficients in subbands 4 19. Concurrence matrix-based texture features are incorporated into the feature vector to further improve the texture classification sensitivity. The concatenated feature vector is then fed into a pretrained genetic neural network classifier which identifies smears by labeling fingerprint subblocks into different categories. Finally DCT decomposition is used to detect abnormalities in fingerprint images containing small smear areas and abrupt breakages. Experimental results indicate that the hybrid method can effectively identify various types of fingerprint smears. 1. Introduction Fingerprint identification has long been used as a key biometric technique in many criminal and civil applications such as crime investigation physical .
