Abstract
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.
Highlights
The application of biometric devices and systems is experiencing significant growth, primarily due to the increasing need for reliable authentication and identification [1]
While code analysis activities established correct implementation, in this activity we looked into how ML algorithm was applied, that is, what are the consequences of using this particular optimization algorithm for fingerprint image registration
The increased use of biometric systems requires additional research efforts related to their reliability estimation
Summary
The application of biometric devices and systems is experiencing significant growth, primarily due to the increasing need for reliable authentication and identification [1]. One of the reasons for adopting this approach was to familiarize ourselves with the code and the algorithms, looking for possible implementation errors first This familiarity, in turn, has been very useful in the process of identifying test cases of particular interest, that is, those that stress the performance of the program and where the algorithm might fail. This approach allowed us to reduce the size of the testing input space and automate the test procedure to achieve greater coverage.
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