Movi-color target analysis based on using minimum distance classification
The demand increased last decades to modify optical photography systems and increase its quality to classify and analyze movement in a video clip. This is very important in many applications like vision computing system (Robots). The process of detection movement of a target is not easy process because it is controlled by many physical parameters like motion, image quality and filming environment. Moreover, it dose effect by the real 3D scene projection on 2D image.
This work focused to study, analyze and classify images of moving targets for different distances (D) between camera and target in the video scene with constant background. Where many statistics properties are calculated and studied like object area (A (i)), object centre (Cx, Cy) and find its function with distance (D). The distance between the target and the camera is estimated accurately depending on target’s area (A) as a function of distance. It is found that there is a good match between the real and the estimated distance depending on mean square difference (MSD=0 - 160.7 x 10-3)