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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Verification and Validation of a Fingerprint Image Registration Software | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 15940 Pages 1-9 DOI 10.1155 ASP 2006 15940 Verification and Validation of a Fingerprint Image Registration Software Dejan Desovski 1 Vijai Gandikota 1 Yan Liu 2 Yue Jiang 1 and Bojan Cukic1 1 Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV26506-6109 USA 2 Motorola Labs Motorola Inc. Schaumburg IL 60196 USA Received 28 February 2005 Revised 14 September 2005 Accepted 21 October 2005 The need for reliable identification and authentication is driving the increased use of biometric devices and systems. Verification and validation techniques applicable to these systems are rather immature and ad hoc yet the consequences of the wide deployment of biometric systems could be significant. In this paper we discuss an approach towards validation and reliability estimation of a fingerprint registration software. Our validation approach includes the following three steps a the validation of the source code with respect to the system requirements specification b the validation of the optimization algorithm which is in the core of the registration system and c the automation of testing. Since the optimization algorithm is heuristic in nature mathematical analysis and test results are used to estimate the reliability and perform failure analysis of the image registration module. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION The application of biometric devices and systems is experiencing significant growth primarily due to the increasing need for reliable authentication and identification 1 . For example fingerprint identification is used at airports for securing border crossing but also in our offices as a password replacement. Typical biometric system classifies users as genuine or imposters depending on a selected threshold. For example if 50 is selected as a threshold for the device whose
