Content-Based Image Retrieval Based on the Multi-Scale Radon Transform
Zhou Li-hua · ACTA PHOTONICA SINICA · 2007
The invariant using statistical theory of Radon transform is constructed and a new kind of image retrieval algorithm based on multi-scale Radon transform is presented.In the first place,the shift invariant is achieved by the central moment on the Radon transform of edge images,which is gained by the wavelet modulus maximum.In the second place,the scaling invariant based on the central moment is deduced after analyzing the statistical characteristics of Radon transform.Since the singular values of matrix are uncorrelated with the position of the column or the row of matrix.Here,this property can be used to get the rotational invariant from the Radon moments.In the third place,the rotational invariant property of singular values on the moment matrix is used to get the rotational invariant.In this way,the character vector with shift,scaling and rotational invariant is constructed in this algorithm.Finally,the Gaussian model is used to normalize the different sub-characters distance to the shape feature of image.The shape similarity of the querying image and other images is computed by the Euclidean distance.Experiments indicate that this method is of robustness to the noises in image′s similarity retrieval and has a higher retrieval-rate than those of Pseudo-Zernike moments,wavelet modulus maximum and Tchebichef moments.