Minutiae Extraction and Finger Print Image Recognition

Alagappa Institute of Skill Development & Computer Centre,Alagappa University, Karaikudi, India.15 -16 February 2017. IT Skills Show & International Conference on Advancements In Computing Resources (SSICACR-2017)

Format: Volume 5, Issue 1, No 16, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: Mrs. S.Subhashini

Reference:IJCS-235

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Abstract

Fingerprint recognition is one of the most well-known and publicized biometrics. Because of finger print uniqueness and consistency over time, fingerprints have been used for identification for more than a century. Though Many systems with minutiae extractor and minutiae matcher are available for minutiae extraction and matching ,it is very difficult to mark all the minutiae accurately as well as rejecting false minutiae because of the presence of noise in fingerprints.. In practise, it is usually difficult to take a good quality fingerprint image, as these may be degraded and corrupted with noise due to many factors including variations in skin and impression conditions. This degradation can result in a significant number of spurious minutiae being created and genuine minutiae being ignored. Image enhancement techniques are employed prior to minutiae extraction to obtain a more reliable estimate of minutiae locations. In recent years, some new methods have been introduced to the finger print image recognition system to recognize finger print images in order to get better results . In this paper, Finger Print Image recognition and a methods used for minutiae extraction and matching , pros and cons of this method are discussed.

References

1. A.K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, Englewood Cliffs, NJ, 1989. 2. Afsar, F.A., Arif, M. and Hussain, M. 2004. Fingerprint Identification and Verification System using Minutiae Matching. In proceedings of the National Conference onEmerging Technologies. 141-146. 3. Akram, M., Nasir, S., Tariq, A., Zafar, I. and Khan, W. S. 2008. Improved Fingerprint Image Segmentation Using New Modified Gradient Based Technique. In proceedings of the2008 Canadian Conference on Electrical and Computer Engineering. Niagara Falls, Canada,001967 – 001972 4. D. Maio, and D. Maltoni, “Direct gray-scale minutiae detection in fingerprints”, IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 19(1), pp. 27-40, 1997. 5. 6. Robert Hastings, “Ridge Enhancement in Fingerprint Images Using Oriented Diffusion”, IEEE Computer Society on Digital Image Computing Techniques and Applications, pp. 245-252, (2007). 7. Eric P. Kukula, Christine R. Blomeke, Shimon K. Modi, and Tephen J. Elliott, “Effect of Human Interaction onFingerprint Matching Performance, Image Quality, and Minutiae Count”, International Conference onInformation Technology and Applications, pp. 771-776, (2008).


Keywords

Image Recognition , finger print, Minutiae, pixel features , Crossing number, Biometrics.

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