High density Efficient Shape Database Classification for Optimized Stationary Transformed Features

shape information have been the primitive image features in shape detection systems. This paper presents a novel framework for shape information, Shape information is captured in terms of edge images computed using Gradient Vector Flow fields. Invariant moments are then used to record the shape features. The combination of shape features between image and conjunction with the Vector Function provide a robust feature set for retrieval. The experimental results show the efficacy of the method. For matching the images an integrated matching scheme, based on most similar highest priority principle is provided. The experimental results are compared with previous works and are found to be encouraging.