Abstract—Real time segmentation of moving regions in image sequences is a fundamental step in many vision systems including automated visual surveillance human-machine interface and very low bandwidth telecommunications. Background identification is a common feature in many video processing systems. One of the most important back ground identification algorithm is the Gaussian Mixture Model algorithm (GMM).On implementation of the Gaussian mixture model on FPGA results in Reduction of the processing capability of the overall system. Trainable Segmentation is adapted to improve the processing capability. After analyzing and evaluating the performance we conclude with several promising directions for future research.

Index Terms—Video segmentation, back ground identification.

R. S. Sabeenian is with ECE Department in Sona College of Technology, Salem, Tamil Nadu, India. He is currently heading the research group named Sona SIPRO (SONA Signal and Image PROcessing Research Centre) centre located at the Advanced Research Centre in Sona College of Technology, Salem.
S. Lavanya is with Jayam College of Engineering and Technology, Dharmapuri (e-mail: laavanyaprakash@gmail.com).

 

Cite:R. S. Sabeenian and S. Lavanya, "High Definition Video Segmentation Techniques-A Review," International Journal of Computer and Electrical Engineering vol. 5, no.6, pp.559-562, 2013.