Content-Based Image Retrieval Based on the Wavelet Transform and Radon Transform

The invariant using Radon transform is constructed and a new image retrieval algorithm based on the wavelet transform and Radon transform is presented. It turns to be getting multi-scale edge images by the wavelet modulus maxima after decomposing the images by the wavelet transform in the algorithm. The Radon invariant is extracted to be the shape feature of image to the multi-scale edge images and the energy of every sub frequency band is extracted to be the texture feature of image. The Gaussian model is used to normalize the different sub-characters distance to the shape feature of image and the texture feature of image separately. The shape similarity of images and the texture similarity of images are computed by the Euclidean distance separately. Finally, the weighted sums of the shape similarity of images and the texture similarity of images can be the similarity between the querying image and other images. Experiments indicate that this method is robustness to the Gaussian noises in image´s similarity retrieval and more effective in the image retrieval than the other algorithms discussed in the paper.