Feature extraction is a critical step for low contrast palmprint recognition. According to the characteristics with obvious palmprint texture features, a block Radon transform method is presented for palmprint feature extraction. Firstly, the method denoises region of interest of the palmprint and reduces dimension with the first-level wavelet decomposition. Then it blocks the low-frequency sub-image to delineate local primary textures. At last, after all the sub-block images are transformed during 70°～140° by Radon transform method, the line integrals obtained constitute feature vector for the image. The method was tested on the basis of UST palmprint image database. From the experimental results of 94% recognition rate, the method can satisfy the application for authentication systems without excessive demands for collection images.