Palm vein hidden under the skin and its distribution feature is hard to be stolen, which makes the palm vein recognition to be a high security biometric authentication method. Contact-less palm vein imaging can avoid the spread of disease, thus expanding the application range of palm vein biometric authentication devices. However, due to the different un-derstanding of the right imaging position and the change of fingers open degree, contact-less palm vein image acquisi-tion led to a certain degree of translation, rotation, scaling and shear, that is, the image deformation. Image deformation causes the imaging feature unstable. In this paper, the effect of image deformation to the stability of palm vein features is studied by some similarity parameters. First, feature points in the palm were marked, contact-less imaging and con-tact imaging of palm vein were acquired. Then, this paper calculated the similarity parameters of the contact-less imag-ing to contact imaging and gave corresponding analysis. Experimental results show that contact-less palm vein imagingwas stable, and derived the linear regression equation of relationship between sample space and the recognition rate: y =?0.000903x + 1.0332, coefficient of determination R2 = 0.9824. This research provided effective and detailed data to the study of contact-less palm vein recognition and gave powerful support to contact-less multi-feature fusion recogni-tion based on hand.