Study of distortion detection and enhancement methods for fingerprint images

Abstract

Image quality degradation and its enhancement is widely studied recently in many research articles in order to deliver best recognition accuracy in presence of poor quality or distorted fingerprinting images as input to fingerprint recognition methods. The distorted or less quality fingerprint images may have the missing and specious features, which may degrade the recognition performance of entire system. Hence it is required for fingerprint recognition system to detect the distorted fingerprint images and then enhance its quality automatically before going to actual recognition functions. The main cause for the false non-match in fingerprint recognition frameworks is fingerprint images elastic distortion. Such research challenge is impacting on complete applications based on fingerprint systems. The scope this paper is limited to presenting the survey on different methods of distortion or poor quality detection in images as well as different methods of image quality enhancement. The goal of this paper is present the complete analysis and review of existing methods presented so far for distortion detection and its quality improvement for further roadmap in this domain. We presented the novel approach for efficient fingerprint distortion detection and mitigation design and framework. The outcome of this paper is the research gap and issues to solve in future works of method designed in this paper.