Object Recognition of a Mobile Robot Based on SIFT with De-speckle Filtering

This paper presents a novel object recognition method, of a mobile robot, by combining scale invariant feature transform (SIFT) and de-speckle filtering to enhance the recognition capability. The main idea of the proposed algorithm is to use SIFT programming to identify other robots after de-speckle filtering process to remove outside noise. Since a number of features are much larger than needed, SIFT method requires a long time to extract and match the features. The proposed method shows a faster and more efficient performance, which enhances localization accuracy of the slave robots. From the simulation results, the method using de-speckle filtering based SIFT shows that the number of features in the extraction process, and that the points in matching process are reduced.