A defocus assessment of palmprint images based on Laplacian sharpening

Defocus problem is an important problem in open uncontrolled palmprint recognition system. Traditional defocus method tries to extract the stable feature. But the accuracy of this method is relatively low for blurred images. This paper proposes a defocus assessment of palmprint images. Firstly, Laplacian sharpening is used to make images clearer. Then, we use Daugman operator assess the image quality and distinguish clear palmprint images from blurred ones. Finally, we remove the blurred images and use the clear ones to be identified. The experiments based on the synthetic blurred palmprint database show a good effect. It demonstrates that this algorithm is an effective approach which can solve the problem of defocus blurred palmprint recognition.