Fingerprint matching based on global orientation field and local features

Author(s):  
Wenzhen Zhou ◽  
Wenzhao Zhang
2005 ◽  
Vol 26 (15) ◽  
pp. 2424-2430 ◽  
Author(s):  
Jin Qi ◽  
Suzhen Yang ◽  
Yangsheng Wang

Author(s):  
JEN-FENG WANG ◽  
CHEN-LIANG LIN ◽  
CHEN-WEN YEN ◽  
YUNG-HSIEN CHANG ◽  
TENG-YI CHEN ◽  
...  

Early detection and intervention strategies for schizophrenia are receiving increasingly more attention. Dermatoglyphic patterns, such as the degree of asymmetry of the fingerprints, have been hypothesized to be indirect measures for early abnormal developmental processes that can lead to later psychiatric disorders such as schizophrenia. However, previous results have been inconsistent in trying to establish the association between dermatoglyphics and schizophrenia. The goal of this work is to try to resolve this problem by borrowing well-developed techniques from the field of fingerprint matching. Two dermatoglyphic asymmetry measures are proposed that draw on the orientation field of homologous fingers. To test the capability of these measures, fingerprint images were acquired digitally from 40 schizophrenic patients and 51 normal individuals. Based on these images, no statistically significant association between conventional dermatoglyphic asymmetry measures and schizophrenia was found. In contrast, the sample means of the proposed measures consistently identified the patient group as having a higher degree of asymmetry than the control group. These results suggest that the proposed measures are promising for detecting the dermatoglyphic patterns that can differentiate the patient and control groups.


2011 ◽  
Vol 403-408 ◽  
pp. 4499-4506 ◽  
Author(s):  
Ravinder Kumar ◽  
Pravin Chandra ◽  
M. Hanmandlu

Singular point detection is the most important step in Automatic Fingerprint Identification System (AFIS) and is used in fingerprint alignment, fingerprint matching, and particularly in classification. The computation of orientation field of a fingerprint can be verified by computing orientation field reliability. The most unreliable portion in orientation field can be the possible location of singular points. In this paper we have proposed a novel algorithm for detecting singular points using reliability of the fingerprint orientation field. Experimental results show that the proposed algorithm accurately detects singular points (core and delta) with the detection rate of 92.6 %.


Author(s):  
Almudena Lindoso ◽  
Luis Entrena ◽  
Judith Liu-Jimenez ◽  
Enrique San Millan

2004 ◽  
Vol 9 (4) ◽  
pp. 435-438 ◽  
Author(s):  
Zhu En ◽  
Yin Jian-ping ◽  
Zhang Guo-min

Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


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