Multiscale relativity algorithm for shape-based image retrieval

Two kinds of image retrieval reference frames are compared mathematically, and it is found that the polar coordinates facilitate processing multi-scale images. The interpolation method for edge sequence points is designed, where two compared clusters edge points are endowed with the same length, and all original characteristic boundary points are reserved. By means of the characters of similar image boundaries with the maximum relativity in the space distance, the multi-scale relativity algorithm for shape-based image retrieval (MSRA) is proposed, which is sensitive to the changed image contours, but insensitive to the image size. Compared with common boundary points Fourier descriptor algorithm (CBPFD), the identification rate of MSRA gets higher 29% than that of CBPFD in the natural image collections and the identification rate of MRASB is almost 2.5 times of that of CBPFD in the artificial image collections.