International Journal of Electrical and Computer Engineering (IJECE) Vol. 8, No. 2, April 2018, pp. 1194~1213 ISSN: 2088-8708, DOI: 10.11591/ijece.v8i2.pp1194-1213  1194 Journal homepage: http://iaescore.com/journals/index.php/IJECE An Efficient Fingerprint Identification using Neural Network and BAT Algorithm Subba Reddy Borra 1 , G. Jagadeeswar Reddy 2 , E.Sreenivasa Reddy 3 1 Department of Computer Science and Engineering, JNTUH, Hyderabad, 500085, India 2 Vaagdevi Institute of Technology and Sciences, Proddatur, AP, 516360, India 3 University College of Engineering, Acharya Nagarjuna University, AP, 522508, India Article Info ABSTRACT Article history: Received Nov 15, 2017 Revised Dec 27, 2017 Accepted Jan 5, 2018 The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor. Keyword: BAT algorithm Classification Histogram equalization Hybridneural network Median filter Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Subba Reddy Borra , Department of Computer Science and Engineering, JNTUH, Hyderabad, 500085, India. Email: bvsr79@gmail.com 1. INTRODUCTION Multi-biometric recognition [1] and biometric template protection [2] are defined in this work to derive developments in the field of biometric recognition. The use of multi-biometric recognition improves the reliability and accuracy compared to the existing biometric system. An Automatic recognition system uses biometric indicator and it produces high error rates [3]. Biometric vendors are used the Multi-biometric system (e.g. fingerprint and finger vein by SAFRAN Morpho1) and it require large data sets (e.g. within the Aadhaar project [4] by the Unique Identification Authority of India (UIDAI)). The multi-biometric system provides multiple information about the same object and it the template of multi-biometric system requires more security. Missing of any information from biometric template delete the person identity and creates security problems. For instance permanency following from claiming subjects without assent [5], [6] alternately remaking from claiming unique biometric qualities (e. G. Fingerprints [7] alternately iris textures may turn into a sensible danger. That biometric format ought a chance to be secured by giving work to protection Also integument about saved biometric information. Format protections schemes give provable security alternately privacy, Furthermore useful recognition rates gotten are elusive, Indeed around little datasets.