Design of Moving Object Detection Algorithm Based on Computer Vision

Image recognition technology of computer vision is one of the hotspots in the research field. The target detection and recognition technology is becoming mature. On the basis of this technology, a moving target capture algorithm with simple and fast operation, resource saving and high potential value is designed. Real-time monitoring is carried out for the object tracking of shell trail. A moving object detection algorithm based on static background was designed and the definition of target image was optimized. Because of the moving target image is not clear, wavelet transform was used to remove noise and wiener filter restoration method was used to remove fuzzy shadows to make the image clear. An appropriate threshold value was selected by image threshold segmentation, and the target was extracted from the background image by differential image binarization. Finally, morphological corrosion and Hough transform are used to calculate the location of moving targets, so as to detect the target of moving shells in the environment, and capture the track of moving target on this basis, which provide a basis for the next step of visual servo control.