Biometric Identification by Fingerprint Image Based Minutiae Detection
Author(s) -
Israa Mohamed Khidher
Publication year - 2009
Publication title -
mağallaẗ al-tarbiyaẗ wa-al-ʻilm
Language(s) - English
Resource type - Journals
eISSN - 2664-2530
pISSN - 1812-125X
DOI - 10.33899/edusj.2009.57707
Subject(s) - minutiae , artificial intelligence , computer science , biometrics , computer vision , fingerprint (computing) , fingerprint recognition , rgb color model , authentication (law) , identification (biology) , sobel operator , pattern recognition (psychology) , image processing , edge detection , image (mathematics) , computer security , botany , biology
In an increasingly digital world, reliable personal authentication has become an important human computer interface application, some Biometric Identification by Fingerprint Image Based Minutiae Detection. 156 examples where establishing a person’s identity. Biometrics is the science of verifying the identity of an individual through physiological measurements or behavioral attributes. Biometrics such as fingerprint, face and voice print offers means of reliable personal authentication. Fingerprints were one of the important forms of biometric identification to be used for law and civilian applications. Data base images for fingerprint images are selected from the First International Fingerprint Verification Competition FVC2000/DB2. Then a primary processing to these images are performed through the transformation from RGB color to binary form using the derivative of Gaussian filter scheme because, the excellence of this scheme in edge detection. The Sobel horizontal and vertical gradient are relied to compute the ridge angle and to detect its orientation, then to detect the details accurately image morphological operations are used for thinning operation. These images are segmented to image portions represented by blocks also to segment the finger tip to image portions contain details assimilate by ridges ending as well ass ridges bifurcation. Indeed, to detect the details of the fingerprint Crossing Number method is relied with the resultant binary portions to test them if they represent ridge ending or ridge bifurcation. The proposed work shows efficient results exceeds 82% compared with other system on the same field.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom