Ankit Jain

Work place: Dept. of Information Technology, Maharaja Surajmal Institute of Technology, GGSIP University, New Delhi, INDIA



Research Interests: Computer systems and computational processes, Image Compression, Image Manipulation, Image Processing


Ankit Jain is pursuing his Bachelor of Information Technology from Maharaja Surajmal Institute of Technology, GGSIPU, New Delhi. Currently, he is doing his major project on Implementation of Touch-less Fingerprint Recognition System. His research interests are biometrics, image processing and fingerprint systems.

Author Articles
Touch-less Fingerprint Analysis — A Review and Comparison

By Prabhjot Kaur Ankit Jain Sonia Mittal

DOI:, Pub. Date: 8 Jun. 2012

Touch-less fingerprint recognition system is a reliable alternative to conventional touch-based fingerprint recognition system. Touch-less system is different from conventional system in the sense that they make use of digital camera to acquire the fingerprint image where as conventional system uses live-acquisition techniques. The conventional fingerprint systems are simple but they suffer from various problems such as hygienic, maintenance and latent fingerprints. In this paper we present a review of touch-less fingerprint recognition systems that use digital camera. We present some challenging problems that occur while developing the touch-less system. These problems are low contrast between the ridge and the valley pattern on fingerprint image, non-uniform lighting, motion blurriness and defocus, due to less depth of field of digital camera. The touch-less fingerprint recognition system can be divided into three main modules: preprocessing, feature extraction and matching. Preprocessing is an important step prior to fingerprint feature extraction and matching. In this paper we put our more emphasis on preprocessing so that the drawbacks stated earlier can be removed. Further preprocessing is divided into four parts: first is normalization, second is fingerprint Segmentation, third is fingerprint enhancement and last is the core point detection. Feature extraction can be done by Gabor filter or by minutia extraction and the matching can be done by Support Vector Machine or Principal Component Analysis and three distance method.

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