Author(s): Roli Bansal, Priti Sehgal & Punam Bedi
Journal: International Journal of Biometric and Bioinformatics
ISSN 1985-2347
Volume: 4;
Issue: 2;
Start page: 71;
Date: 2010;
VIEW PDF
DOWNLOAD PDF 
Original page
Keywords: Biometrics | fingerprint image | minutiae extraction | Hit or Miss transform | mathematical morphology
ABSTRACT
Fingerprints are the most widely used parameter for personal identification amongst allbiometrics based personal authentication systems. As most Automatic FingerprintRecognition Systems are based on local ridge features known as minutiae, markingminutiae accurately and rejecting false ones is critically important. In this paper we proposean algorithm for extracting minutiae from a fingerprint image using the binary Hit or Misstransform (HMT) of mathematical morphology. We have developed and tested structuringelements for different types of minutiae present in a fingerprint image to be used by the HMTafter preprocessing the image with morphological operators. This results in efficient minutiaedetection, thereby saving a lot of effort in the post processing stage. The algorithm is testedon a large number of images. Experimental results depict the effectiveness of the proposedtechnique.
Journal: International Journal of Biometric and Bioinformatics
ISSN 1985-2347
Volume: 4;
Issue: 2;
Start page: 71;
Date: 2010;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Biometrics | fingerprint image | minutiae extraction | Hit or Miss transform | mathematical morphology
ABSTRACT
Fingerprints are the most widely used parameter for personal identification amongst allbiometrics based personal authentication systems. As most Automatic FingerprintRecognition Systems are based on local ridge features known as minutiae, markingminutiae accurately and rejecting false ones is critically important. In this paper we proposean algorithm for extracting minutiae from a fingerprint image using the binary Hit or Misstransform (HMT) of mathematical morphology. We have developed and tested structuringelements for different types of minutiae present in a fingerprint image to be used by the HMTafter preprocessing the image with morphological operators. This results in efficient minutiaedetection, thereby saving a lot of effort in the post processing stage. The algorithm is testedon a large number of images. Experimental results depict the effectiveness of the proposedtechnique.
