Comprehensive Analysis of Object Detection through Segmentation

Abstract

In computer vision extracting an object from an image automatically is too hard. Towards addressing this issue a comprehensive analysis of most of the Object detection through different Segmentations is performed taken from the major recent publications covering various aspects of the research in this area. We identify the following methods of the state-of-the-art techniques in which an object can be detected: (1) Mean Shift Segmentation With Region Merging, (2) Boundary Structure Segmentation With Region Grouping, (3) Watershed Segmentation With Region Merging. All these are semi automatic detection of an object through segmentation and contour based shape descriptor. The results tabulated prove that the Mean Shift Segmentation with Region Merging Process yields the best result over the other two methods in detection the Object Of Interest.