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With the continuous rapid development of biometric technology, dorsal hand vein recognition technology has been more and more widely used in all fields. Because of the influence of the different hardware conditions and environment, the recognition rate is reduced. For the problem of brightness, rotation, scales of the dorsal hand vein images, we propose a method of dorsal hand vein recognition based on multi-angle rotation integration and discrete cosine transform, and the parameter is optimized. We combine a method of image-binary-segmentation which is based on the gradient enhancement, select the best angle interval for the rotation integration, intercept best feature matrix for classification recognition after two-dimensional discrete cosine transform, the recognition rate is more than 99.9%. The experiment verifies the feasibility and superiority of the method proposed in this paper by comparing the recognition effects of other traditional algorithm of dorsal hand vein images.