Developing Video and Image Processing Systems: Video Reading and Target Background Extraction

When developing video and image processing systems using MATLAB and Simulink, video reading and target background extraction can be implemented to achieve enhanced functionality and effects. For instance, image processing algorithms can be utilized for object detection and tracking – typically involving techniques like background subtraction using functions such as vision.ForegroundDetector or implementing Gaussian Mixture Models (GMM) for dynamic background modeling. Video filters and special effects can be applied through Simulink blocks like Vision.VideoFilter or custom MATLAB code using imfilter functions to enhance visual quality. Furthermore, deep learning techniques can be integrated for image classification and recognition tasks, leveraging MATLAB's Deep Learning Toolbox with pre-trained networks like YOLO or ResNet for more accurate and intelligent image processing. By combining MATLAB's computational capabilities with Simulink's visual programming environment, developers can create diverse video and image processing applications that meet various domain-specific requirements, from real-time surveillance systems to medical imaging analysis.