i-manager Publications

Efficient Real Time Inked Fingerprints Identification System

C. Naga Raju*, Vijaya Kumar**, R. Pradeep Kumar Reddy***

* Associate Professor and Head, Department of Computer Science and Engineering, YSR Engineering College Andhra Pradesh, India.

** Assistant Professor, Department of Computer Science Engineering, Rajeev Gandhi Memorial College of Engineering and Technology, Nandyal, Andhra Pradesh, India.

*** Assistant Professor, Department of Computer Science and Engineering, YSR Engineering College, Andhra Pradesh, India.

Periodicity:June - August'2014
DOI : https://doi.org/10.26634/jpr.1.2.2924

Abstract

With the increase in technology threats to personal data, security has been increased. There was a need to introduce a technology that secures our data more efficiently from other unlawful intervention. Automatic Fingerprint Recognition Systems are more powerful and widely used for criminal identification and authentication. Automatic fingerprint recognition is an extremely critical process, especially in low quality and rotation invariant inked and scanned fingerprints because of the quality of ink and the way of finger impression on the surface of the paper or scanner. In this paper, an efficient real time fingerprint identification system for inked fingerprints has been addressed. This method ensures the quality of the fingerprint with greater matching reliability and efficiency.

Keywords

ROI (Region of Interest), AFIS (Automatic Fingerprint Identification System), Minutiae, Geometric Mean and Classification

How to Cite this Article?

Raju, C. N., Kumar, V., and Reddy, R. P. K. (2014). Efficient Real Time Inked Fingerprints Identification System. i-manager’s Journal on Pattern Recognition, 1(2), 16-23. https://doi.org/10.26634/jpr.1.2.2924

References

[1]. L. Jinxiang, H. Zhongyang, and C. KapLuk, (2000). “Direct minutiae extraction from gray-level fingerprint image by relationship examination”. In International Conference on Image Processing (ICIP), Vol.2, pp.427–430.

[2]. B. Bir and T. Xuejun, (2003). “Fingerprint indexing based on novel features of minutiae triplets”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.25(5), pp.616–622.

[3]. A. K. Jain, L. Hong, and B. R., (1997). “On-line fingerprint verification”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.19(4), pp.302–314.

[4]. Adrian Lim Hooi Jin et. al, (2002). “Fingerprint Identification and Recognition Using Backpropagation Neural Network”. Students Conference on Research and Development Proceedings, IEEE, 2002.

[5]. G.SambasivaRao, C. NagaRaju, L. S. S. Reddy and E.V. Prasad, (2008). “A Novel Fingerprints Identification System Based on the Edge Detection”. International Journal of Computer Science and Network Security, Vol.8, pp.394-397.

[6]. Haiping Lu, Xudong Jiang and Wei-Yun Yau, (2002). “Effective and Efficient Fingerprint Image Post processing”. International Conference on Control, Automation, Robotics and Vision, Vol.2, pp.985- 989.

[7]. I. Plajh, M. Cifrek, S. Tonkovic, (2003). “Characteristics and Application of the Fingerprint Recognition Systems”. Measurement Science Review, Vol.3, No.2.

[8]. JinweiGu, Jie Zhou, and Chunyu Yang, (2006). “Fingerprint Recognition by Combining Global Structure and Local Cues”. IEEE Transactions on Image Processing, Vol.15, No.7, pp.1952–1964.

[9]. Robert Hastings, (2007). “Ridge Enhancement in Fingerprint Images Using Oriented Diffusion”. IEEE Computer Society on Digital Image Computing Techniques and Applications, pp.245-252.

[10]. Ching-Tang Hsieh and Chia-Shingu, (2007). “Humanoid Fingerprint Recognition Based on Fuzzy Neural Network”. International Conference on Circuit, Systems, Signal and Telecommunications, pp.85-90.

[11]. Liu Wei, (2008). “Fingerprint Classification using Singularities Detection”. International Journal of Mathematics and Computers in Simulation, Vol.2, No.2, pp.158-162.

[12]. Hartwing Fronthaler, Klaus kollreider, and Josef Bigun, (2008). “Local Features for Enhancement and Minutiae Extraction in Fingerprints”. IEEE Transactions on Image Processing, Vol.17, No.3, pp.354- 363.

[13]. Alessandra Lumini, and Loris Nann, (2008). “Advanced Methods for Two-Class Pattern Recognition Problem Formulation for Minutiae-Based Fingerprint Verification”. Journal of the Pattern Recognition Letters, Vol.29, pp.142-148.

[14]. Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, and Parvinder S. Sandhu, (2008). “Fingerprint Verification System using Minutiae Extraction Technique”. Proceedings of World Academy of Science, Engineering and Technology, Vol.36, pp.497-502,

[15]. J. Venkatesh and V. D. Ambeth Kumar, (2013). ”Advanced Filter and Minutia Matching For Fingerprint Recognition”. International Journal of Science and Research (IJSR), Vol.2 No.1.

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.