The Simplest Implementation of Background Frame Difference Method

This is the simplest MATLAB source code implementation for the background frame difference method. Frame difference is a pixel-change-based background segmentation approach commonly used for object detection and tracking in video sequences. The core algorithm operates by extracting pixel-wise differences between consecutive frames, then applying thresholding to separate static background from moving foreground objects.

In this source code implementation, we first read the video file using MATLAB's video reading functions. Each frame is converted to grayscale using rgb2gray function to reduce computational complexity. The key step involves using imabsdiff function to calculate absolute differences between current and previous frames. The resulting difference image undergoes thresholding via im2bw (or modern equivalent imbinarize) to create a binary mask. For noise reduction, bwareaopen function removes small connected components below a specified pixel area threshold. Finally, bwlabel performs connected component labeling to identify distinct objects for further processing and analysis.

This foundational implementation demonstrates basic concepts of frame differencing, making it particularly suitable for beginners to understand algorithm workflow and MATLAB's image processing toolbox functions for motion detection applications.