A finger vein image quality assessment method using object and human visual system index

Authors:
Hui Ma;Kejun Wang;Linlin Fan;Fengpeng Cui
Affiliations:
College of Electronic Engineering, Heilongjiang University, Harbin, China;College of Automation, Harbin Engineering University, Harbin, China;College of Electronic Engineering, Heilongjiang University, Harbin, China;China Ship Heavy Industrial Group Company 703th Research Institute, Harbin, China
Venue:
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2012

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Abstract

A finger vein image quality assessment method which uses object and human visual system index is proposed. This is based on both the human visual characteristics and finger vein image characteristics captured by the use of contactless and near infrared rays. We present an HSNR (signal to Noise ratio based on human visual system) finger vein image quality evaluation index by simulating the human visual system, and integrating the HSNR with effective area score, clarity score, finger shifting score and contrast score to obtain the total image quality score of the finger vein image. Experimental results demonstrate that the proposed method is consistent with subjective assessment by humans, and thus can be used to describe the visual perception of the image effectively.