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In computer vision and video processing areas, moving object detection is a very important research topic. The process of moving object detection in video consists of two steps - background extraction and moving object detection. The preliminary idea is to capture a series of video pictures at regular intervals; the video is divided into n number of frames to describe the vector information of the region. The segmented frames are RGB in nature. So it should be converted into YBCBR or Grayscale images for better performance. The idea is to implement moving object detection in real time execution. The experiments show that detected objects in real streaming video is converted into drawing shapes or figures in a specified area.