Abstract: The V-system is a special orthogonal multiwavelet.Due to the virtue of its orthogonality and multi-resolution, only a small number of basis functions are required to describe characteristics of a signal.And multi level features of the signal, from any coarse scale to a finer scale, can be obtained by increasing the number of basis functions.This paper applies this characteristic of the V-system on shape similarity retrieval, and a new shape retrieval algorithm, V-algorithm, is achieved by combing its boundary features and region features.First, the boundary of the image is extracted and orthogonally decomposed into a V-series, thereby obtaining a boundary feature vector consisting of the V-descriptors.Meanwhile, a region feature vector of the image is obtained by applying the Vtransform to the image region.Then similarity between shapes is measured using an integrated shape descriptor, which combines the boundary features and region features.The results of experiments conducted on four benchmark databases show that the method in this work has advantage in retrieval efficiency in comparison with several classical algorithms.