Int. J. Biometrics, Vol. 11, No. 2, 2019 177 Copyright © 2019 Inderscience Enterprises Ltd. Fake fingerprint liveness detection based on micro and macro features Rohit Agrawal and Anand Singh Jalal* GLA University, Mathura, 281406, India Email: rohit.agrwal@gla.ac.in Email: asjalal@gla.ac.in *Corresponding author K.V. Arya Institute of Engineering and Technology, Lucknow, 226021, India Email: kvarya@ietlucknow.ac.in Abstract: Fingerprint is the most hopeful biometric authentication that can specifically identify a person from their exclusive features. In the proposed approach, a novel software-based classification method is presented to classify between fake and real fingerprint. The intention of the proposed system is to improve the security of biometric identification system. The statistical techniques are good for micro features but not well for macro. In this paper, we present a novel combination of local Haralick micro texture features with macro features derived from neighbourhood gray-tone difference matrix (NGTDM) to generate an effective feature vector. Combined extracted features of training and testing images are passed to support vector machine for discriminating live and fake fingerprints. The proposed approach is experimented and validated on ATVS dataset and LivDet2011 dataset. The proposed approach has achieved good accuracy and less error rate in comparison with previously studied techniques. Keywords: biometrics; fingerprints; liveness; spoof; micro features; macro features. Reference to this paper should be made as follows: Agrawal, R., Jalal, A.S. and Arya, K.V. (2019) ‘Fake fingerprint liveness detection based on micro and macro features’, Int. J. Biometrics, Vol. 11, No. 2, pp.177–206. Biographical notes: Rohit Agrawal received his MTech in Computer Science from the UPTU Lucknow, India. He is pursuing his PhD in the area of computer vision from the GLA University Mathura, India. He has 15 years of teaching experience and currently, he is working as an Assistant Professor in the Department of Computer Engineering and Applications, GLA University, Mathura, India. His research interests include image processing and computer vision. Anand Singh Jalal received his MTech in Computer Science from the Devi Ahilya Vishwavidyalaya, Indore, India. He received his PhD in the area of computer vision from the Indian Institute of Information Technology (IIIT),