MATLAB Image Differencing Implementation for Human Tracking

This document presents the implementation of human tracking using image differencing techniques in MATLAB. The algorithm accurately detects and records coordinates of target objects in video frames, enabling comprehensive analysis of human movements. By employing background subtraction methods - where consecutive frames are compared to identify moving pixels - the system captures target movement trajectories throughout video sequences. This implementation utilizes MATLAB's Image Processing Toolbox functions such as imabsdiff() for frame differencing and regionprops() for coordinate extraction. The technical approach involves converting frames to grayscale, applying Gaussian blur to reduce noise, computing absolute differences between frames, and applying thresholding to isolate moving objects. This advanced technique finds extensive applications in surveillance systems, while also serving important roles in sports training analysis and medical movement studies. The implementation of human tracking through image differencing with coordinate recording in video frames represents a significant and practical technical achievement with broad research implications.