Study of Altered Fingerprint Detection Using Artificial Neural Network
Abstract: Fingerprint Identification has been the most widely used measure for biometric identification. But as there have been techniques to counter every technology, altered fingerprinting has also emerged as the way to counter the AFIS which is a system to identify the fingerprints. The currently used fingerprint quality assessment software is unable to detect most of the altered fingerprints since the image quality does not always degrade due to alteration. This paper discusses 1) Types of fingerprint alterations 2) Techniques for detection of altered fingerprints 3) Implementation of artificial neural network in fingerprint identification 4) Minutiae extraction using neural network. The use of the suggested techniques can help to mitigate the incidents of altered fingerprints and can detect them to an increased extent.
Keywords: Obliteration, Distortion, Imitation, Binarization, Skeletonization, Artificial Neural Network, Back Propagation, Minutiae, Scar, Ridge
How to Cite?: Pravin Keshav Patil, Sandip S. Patil, N. P. Jagtap, "Study of Altered Fingerprint Detection Using Artificial Neural Network", Volume 4 Issue 1, January 2015, International Journal of Science and Research (IJSR), Pages: 2471-2473, https://www.ijsr.net/getabstract.php?paperid=SUB15898, DOI: https://dx.doi.org/10.21275/SUB15898