MATLAB Implementation of Frame Difference Method for Target Detection

The frame difference method is a simple yet efficient approach for moving target detection, particularly suitable for video surveillance scenarios. Its core principle involves identifying moving objects by analyzing differences between consecutive frames in a video sequence.

Implementing the frame difference method in MATLAB typically involves the following steps: First, read video or image sequences and convert each frame to grayscale to reduce computational load. Then calculate the absolute difference between two or three consecutive frames. Apply thresholding to binarize the difference image, obtaining a rough outline of moving targets. Finally, use morphological operations (such as erosion and dilation) to remove noise and connect broken regions.

Key MATLAB functions involved include VideoReader for video input, rgb2gray for color conversion, imabsdiff for frame differencing, and imbinarize with appropriate threshold values. The algorithm's efficiency comes from its simplicity, requiring minimal processing per frame compared to more complex methods.

While the frame difference method offers straightforward implementation and high computational efficiency, it's sensitive to lighting changes and may produce "ghosting" effects when objects move too slowly. Improved versions can incorporate background modeling or optical flow methods to enhance detection accuracy. Beginners can use this method to quickly grasp the fundamental concepts of motion detection in computer vision applications.