Segmentation for finger vein image based on PDEs denoising

This paper puts forward a variation model based the fourth-order PDE and the second-order PDE for finger-vein image denoising, which increases the Peak Signal to Noise Ratio (PSNR) by 2dB, and better maintains the edge of image. A midpoint threshold segmentation method is also employed in this paper, which can extract the target effectively. By experimental verifications for the synthetic and real finger-vein images, a comparative research with the three universal segmentation methods has been extended.