Assessing face image quality for smartphone based face recognition system

In recent years, the popularity of smartphones has increased massively as a personal and authentication device. Face based biometrics is being used to secure the device and control access to several different services via smartphones such as payment gateways etc. Thus, to maintain the reliability and to obtain better verification performance, there is a need to adopt the standards recommended for face sample quality. In this paper, we present an evaluation of face image quality assessment using well-established ISO standards on the images collected using smartphones. In this work, we constructed a new database of 101 individuals with 22 frontal face images with different facial pose angles, illumination and at five different distances between the subject and the mobile device. We evaluate the existing quality metrics and further propose a new quality metric based on vertical edge density that can robustly estimate the pose variations and improves the quality estimation of a face image. The proposed method is evaluated for reliable estimation of the quality for smartphone face biometrics.

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