International Journal of Electronics Signals and Systems


Video surveillance has been a popular security tool for years. Video surveillance systems produce huge amounts of data for storage and display. Long-term human monitoring of the acquired video is impractical and in-effective. This paper presents a novel solution for real-time cases that identify and record only “interesting” video frames containing motion. In addition to traditional methods for compressing individual video images, we could identify and record only “interesting” video images, such as those images with significant amounts of motion in the field of view. The model would be built in simulink, one of tools in matlab and incorporated with davinci code processor, a video processor. That could significantly help reduce the data rates for surveillance-specific applications.



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