The object recognition based on Scale-Invariant feature transform and hybrid segmentation

This paper deals with research in the area of image analysis. Our approach is based on hybrid segmentation and Scale-Invariant Feature Transform (SIFT) method. The main idea is to improve the process of object recognition and their classification into classes by Support Vector Machine (SVM) classifier. The fast and powerful hybrid segmentation algorithm based on Mean Shift and Believe Propagation principles is used to improve object classification. Finally, the image segmentation algorithm was integrated with SIFT descriptor. The developed method was tested on real unsegmented and segmented images.