matlab行人检测 程序源码.zip

% Approximate Median Filter background model for moving object segmentation. %采用近似中值滤波背景模型参考图像实现运动目标分割 clear all; close all; % Construct a videoreader class to read a avi file, first the 'car_parking.avi' , % then the ‘highwayII_raw.avi'. videoObj = VideoReader('ddd.mp4'); numFrames =videoObj.NumberOfFrames; %Get the speed of the AVI movie in frames per second (fps) FPS = videoObj.FrameRate; % Read the first frame in the video sequence as the initial value newframe = read(videoObj, 10); fmed = double(newframe); % Get the height, width, and number of color components of the frame [height, width, numColor] = size(newframe); % Assign a value to the threshold Threh = 60; beta = 0.6; fg = false(height, width); %创建方形结构元素，用于对分割结果形态学滤波 se = strel('square',3); % To avoid consuming too much memories, read only a one frame each time. for n = 1:numFrames newframe = read(videoObj, n); % Calculate the differrence image between the new frame and fmed Idiff = double(newframe) - fmed; % Update the median of each pixel value pixInc = find(Idiff > 0); fmed(pixInc) = fmed(pixInc) + beta; pixDec = find(Idiff < 0); fmed(pixDec) = fmed(pixDec) - beta; % Motion segment, detection moving object by threholding Idiff fg = abs(Idiff) >Threh; if ( numColor == 3) % color image fg = fg(:, :, 1) | fg(:, :, 2) | fg(:, :, 3); end %对分割结果进行形态学滤波 fg2 = imopen(fg,se); fg2 = imclose(fg2,se); figure(1); subplot(1,3,1), imshow(newframe); title(strcat('Current Image, No. ', int2str(n))); subplot(1,3,2), imshow(fg); title('Segmented result using Approximate Median Filter'); subplot(1,3,3), imshow(fg2); title('Segmented result using morphological filter'); end %------------------------------------------------------------------