A video object generation tool allowing friendly user interaction

In this paper we describe an interactive video object segmentation tool developed in the framework of the ACTS-AC098 MOMUSYS project. The Video Object Generator with User Environment (VOGUE) combines three different sets of automatic and semi-automatic-tool (spatial segmentation, object tracking and temporal segmentation) with general purpose tools for user interaction. The result is an integrated environment allowing the user-assisted segmentation of any sort of video sequences in a friendly and efficient manner.Peer ReviewedPostprint (published version

Brain Tumor Segmentation: A Comparative Analysis

Five different threshold segmentation based approaches have been reviewed and compared over here to extract the tumor from set of brain images. This research focuses on the analysis of image segmentation methods, a comparison of five semi-automated methods have been undertaken for evaluating their relative performance in the segmentation of tumor. Consequently, results are compared on the basis of quantitative and qualitative analysis of respective methods. The purpose of this study was to analytically identify the methods, most suitable for application for a particular genre of problems. The results show that of the region growing segmentation performed better than rest in most cases.Comment: 8 Pages, 8 Figues, International Journal of Computer Science (IJCSI

Object Detection and Tracking using Watershed Segmentation and KLT Tracker

In this paper a moving object is extracted from a video using video object detection algorithm based on spatial and temporal segmentation The technique begins with temporal segmentation in which edge map is extracted using edge operator The initial binary mask is obtained by using morphological operation applied on initial edge map The next phase is spatial segmentation where gradient image is obtained by multi-scale morphological operator The modified gradient image is obtained by the operator applied over the current frame At last moving object is extracted by precisely and accurately by watershed segmentation which is performed on the modified gradient image Again morphological operation is applied on the output to get final binary mask This binary mask is then complemented to yield the contour line of the video object Using the binary mask the video object is extracted from the video frames After detection of video object the object tracking is performed using Kanade Lucas Tomasi KLT feature tracke