Open Access Open Access  Restricted Access Subscription or Fee Access

A Novel Method for Fingerprint Feature Extraction

Ramandeep Kaur, Amit Kamra, Vijay Dhir

Abstract


Fingerprint recognition is a method of biometric authentication that uses pattern recognition techniques[1] based on high-resolution fingerprints images of the individual. Fingerprints have been used in forensic as well as commercial applications for identification as well as verification. The fingerprint surface is made up of a system of ridges and valleys. The steps for Fingerprint recognition include image acquisition, preprocessing, feature extraction and matching[2]. In the present work, a new fingerprint feature detection algorithm has been proposed. It has been found that presence of noise in fingerprint images leads to spurious minutiae. To overcome this problem, feature extraction has been done which efficiently determine the minutiae points in fingerprint [1]. The proposed method can be used in matching the template for finding bifurcation and termination. The new smoothing algorithm is proposed for the detection of the features of fingerprints. A method has been introduced for finding ridges in the fingerprint image with the help of eight different masks. It is a process of making a binary image of ridges from the grayscale fingerprint image. The experimental results showed the accuracy of the algorithm in terms of genuine acceptance rate, false rejection rate, false acceptance rate.

Keywords


Bifurcation, Orientation Field, Ridges Segmentation and smoothing, termination.

Full Text:

PDF

References


C. Mares ,M. Sepasian and W. Balachandran (2008),” Image Enhancement for Fingerprint Minutiae-Based Algorithms Using CLAHE, Standard Deviation Analysis and Sliding Neighborhood”, Proceedings of The World Congress on Engineering and Computer Science 2008, pp1199-1203.

Chikkerur (2005),”online fingerprint verification system”, Digital Electronics Letters Vol 3, No. 27, pp.:296 – 298.

D. Suter and A. Bab-Hadiashar (2002), “Fingerprint Segmentation using the Phase of Multiscale Gabor Wavelets”, Proceedings of the Fifth Asian Conference on Computer Vision, pp.27-32.

Espinosa Duro , V. (2001) “Minutiae Detection Algorithm for Fingerprint Recognition”, Polytechnic University of Catalonia, Electronic and Automatic Department, IEEE 2001, pp. 264-266.

Hastings, Robert.(2007),”Ridge Enhancement in Fingerprint Images Using Oriented Diffusion”, Digital Image Computing Techniques and Applications, 9th Biennial Conference of the Australian Pattern Recognition Society on Vol 3, No.5 ,pp.245 – 252.

Hong. L., Jain Anil,Yifei wan.(1998), “Fingerprint image enhancement:algorithm and performance” ,IEEE tansactions on pattern analysis and machine intelligence, Vol. 20 no.8,pp.777-789.

Hong-cai Zhang., Miao-li.(2005),”A Gabor filter based fingerprint enhancement algorithm in wavelet domain” . IEEE Conference pp 1205-1214.

Jain Anil, Maltoni David, Maio Dario, (2006) “The Handbook of fingerprint recognisation” Fourth Edition, CRC Press.

Security Technical Report, Vol. 3, No. 1.

Lu, H., Jiang, X. and Yau Wei-Yun (2002), “Effective and Efficient Fingerprint Image Post processing”, 7th International Conference on Control, Automation, Robotics and Vision (ICARCV), Vol. 2, pp. 985-989.

Paul, A.M.; Lourde, R.M (2006),”A Study on Image Enhancement Techniques for Fingerprint Identification”, Video and Signal Based Surveillance, 2006. AVSS apos;06.IEEEInternationalConference,Vol.5 , No.456 ,pp.16 – 20.

Ziad Abu-Faraj and Abdallah Atie. (2000), “Fingerprint identification software for forensic applications”, Proceeding of the IEEE, Piscataway, NJ, USA, Vol. 85, pp1348-1363.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.