Blur kernel estimation to improve recognition of blurred faces

This paper proposes an efficient blind deconvolution method to deblur face images for face recognition. The method involves a salient edge map construction, blur kernel estimation and face image deconvolution. The combined Yale and Extended Yale face database B containing different illumination changes and blur conditions are used to evaluated the face identification system. The results show that the accuracy of the face recognition systems implemented with the proposed method improves the accuracy when the faces are degraded by blur in general and motion blur in particular.