Hawkeye: Cloud Computing Based Automated Video Error Detection in Real-Time

With the rapid development of video surveillance and broadcast systems monitoring the video quality becomes an important aspect to assure a better quality of service. Error detection is an important technique to measure the quality of videos transmitted over the unreliable network. With the advent of HDTV previously subtle errors in videos are becoming more prominent. In this paper, we want to propose a next generation cloud-based video error detection system using image/video processing technology for making the detection process real-time. At first, we introduce an automatic video error detection method and then propose a cloud computing platform. Finally, we integrate error detection method with cloud computing platform named Hawkeye to achieve a real-time video error detection system which ensures contents integrity and minimizes testing time and efforts required to keep ahead of other conventional quality check system. Extensive experiments on prominent datasets and telecasted videos show that the proposed algorithm is very much efficient to detect errors for video broadcast and surveillance applications in terms of computation time and the detection of distorted frames.