Abstract: To classify the scaled and rotated texture images correctly, this paper proposes a new algorithm for texture classification by combining Radon transform and the V-system. We firstly use the Radon transform to convert the image rotation into the image translation, and then apply the V-transform on the image obtained after Radon transform. The energies of the image on different levels under the V-system are expressed by performing a series of downsampling process due to the multi-wavelet characteristics of the V-system. These obtained energies are used as the texture feature description. The feature description method in this paper is robust to the image scaling and rotation because of the multi-resolution characteristics of the V-system and elimination of rotation by applying Radon transform. Results of the experiments conducted on the standard texture datasets show that the proposed algorithm provides superior performance.