Object Recognition based on Graph theory and Redundant Keypoint Elimination Method

Object Recognition System is widely used in different real-life applications such as content-based image retrieval, object detection, etc. In this article, we suggest a noveltechnique for object detection using Redundant Keypoint Elimination method SIFT- Graph Transformation Matching (RKEMSIFT-GTM). This proposed approach deletes redundant points and eliminates false matches. The proposed improved region-growing, which is a powerful method, is used for the final detection stages. The suggested approach is evaluated on datasets such as COIL-۱۰۰ and obtained a good recognition rate compared to other detection methods.

Keywords:

Object Recognition , matching , SIFT , GTM.