ICA Feature Extraction and Recognition for Video Processing

In my graduation project, I developed a comprehensive video processing system based on Independent Component Analysis (ICA) for feature extraction and pattern recognition. The system architecture comprises multiple specialized modules: a video binarization source program that converts frames to binary format using adaptive thresholding algorithms, a frame processing module that handles individual video frames through preprocessing techniques including noise reduction and enhancement, and a robust video tracking source program implementing motion detection and object following mechanisms. Additionally, I created a sophisticated video application specifically designed for gesture tracking and recognition, which employs ICA algorithms to extract distinctive features from hand movements and machine learning classifiers for accurate gesture identification. This application formed the core of my master's degree graduation project, with complete implementation details, algorithm descriptions, and performance analysis meticulously documented in a comprehensive Word document. The system demonstrates effective integration of computer vision techniques with statistical signal processing methods for practical gesture recognition applications.