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With the advancement in modern video processing technologies, the requirement of an efficient coding algorithm for compressing the video data in a huge surveillance system is necessary. The video data rate in a surveillance system plays a crucial role in determining the performance of the compression algorithm. In this paper, a novel compression algorithm for effectively compressing the video inputs from the surveillance systems is presented. The traditional methods fail to eliminate the redundancies in the video input, and can’t meet the current requirement standards in the modern technologies. This results in the increased storage requirement for input video and also makes it time-consuming in processing the video input in real time. In order to overcome the above issues, the proposed algorithm made sufficient modification in the traditional run length coding algorithm by encoding the frames and removing the redundancies using the texture information similarity in the surveillance video, thereby achieved a better compression rate of 50% for a huge dataset of surveillance videos when compared to existing methodologies.
V. R. Prakash (Tue,) studied this question.