Retrieve the similar matching images using reduced SIFT with CED algorithm

Abstract

The local feature descriptor called SIFT, is one of the most widely used descriptors. The keypoints found with RSIFT and describe them in a standard way, which makes them invariant to the size changes, rotation, position, scale, and so on. These are quite powerful features and are used in a variety of tasks. This local feature SIFT descriptor gives potential key points, which are extracted from the image. If there are many such key points, a lot of computation time will be required for the matching key points, and some cases one key point matches more than once. For these reasons, here we have tried to reduce the key points in order to cluster the number of key points. The reduced SIFT with Canny Edge Detection (CED) algorithm can easily identify and trace the specified image from large the Database images as much fast as possible.