基于matlab的运动目标检测系统【源码49期】

matlab代码

252人浏览 · 2026-07-22 22:51:16

matlab代码 · 2026-07-22 22:51:16 发布

一、项目简介

本系统基于MATLAB计算机视觉工具箱，设计并实现了一个视频运动目标检测系统。系统包含图形用户界面模块（object_detect.m与object_detect.fig），用户可通过界面按钮选择AVI或MP4格式视频文件，并采用四种不同的运动目标检测算法进行前景提取：帧差法（pushbutton2回调）通过相邻帧差分实现快速检测；三帧差分法（pushbutton6回调）利用三帧图像的两两差分取最小值，有效减少“双影”现象；混合高斯模型（GMM）（pushbutton8回调）为每个像素建立K个高斯分布，通过自适应更新权值、均值和标准差实现复杂场景下的背景建模；ViBe算法（pushbutton9回调）采用随机样本库初始化，基于像素级邻域一致性进行前景分割。系统支持视频播放过程中的暂停、继续、停止及退出操作，并在界面中实时显示当前处理帧数。

二、部分源码

function pushbutton2_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton2 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

videoName = get(handles.edit1, 'String');

videoSource = vision.VideoFileReader(videoName,...

'ImageColorSpace', 'RGB', 'VideoOutputDataType', 'uint8');

videoInfo = info(videoSource);

videoRate = videoInfo.VideoFrameRate;

waitTime = 1.0/videoRate;

frame_last = rgb2gray(step(videoSource));

count = 1

global exit_flag;

global pause_flag;

exit_flag = false;

pause_flag = false;

while ~isDone(videoSource) && ~exit_flag

if pause_flag

uiwait(handles.figure1);

end

frame = step(videoSource);

frame_now = rgb2gray(frame);

frame_now = medfilt2(frame_now);

frame_diff = abs(frame_now - frame_last);

fgMask = imbinarize(frame_diff);

fgMask = imopen(fgMask, strel('rectangle', [3, 3]));

fgMask = imfill(fgMask, 'holes');

frame_last = frame_now;

axes(handles.axes1);

imshow(frame);

axes(handles.axes2);

imshow(fgMask);

pause(waitTime - 0.02);

count = count + 1

set(handles.edit2,'String',count);

end

release(videoSource);

% --- Executes on button press in pushbutton3.

function pushbutton3_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton3 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

global exit_flag;

exit_flag = true;

% --- Executes on button press in pushbutton4.

function pushbutton4_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton4 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

global pause_flag;

pause_flag = true;

% --- Executes on button press in pushbutton5.

function pushbutton5_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton5 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

global pause_flag;

pause_flag = false;

uiresume(handles.figure1);

% --- Executes on button press in pushbutton6.

function pushbutton6_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton6 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

videoName = get(handles.edit1, 'String');

videoSource = vision.VideoFileReader(videoName,...

'ImageColorSpace', 'RGB', 'VideoOutputDataType', 'uint8');

videoInfo = info(videoSource);

videoRate = videoInfo.VideoFrameRate;

waitTime = 1.0/videoRate;

count = 1;

frame_first = rgb2gray(step(videoSource));

frame = step(videoSource);

global exit_flag;

global pause_flag;

exit_flag = false;

pause_flag = false;

while ~isDone(videoSource) && ~exit_flag

if pause_flag

uiwait(handles.figure1);

end

% 显示该帧图像

axes(handles.axes1);

imshow(frame);

frame_second = rgb2gray(frame);

frame = step(videoSource);

frame_third = rgb2gray(frame);

frame_diff1 = abs(frame_second - frame_first);

frame_diff2 = abs(frame_third - frame_second);

fgMask = imbinarize(min(frame_diff1,frame_diff2));

fgMask = imopen(fgMask, strel('rectangle', [3, 3]));

fgMask = imfill(fgMask, 'hole');

frame_first = frame_second;

axes(handles.axes2);

imshow(fgMask);

pause(waitTime - 0.02);

count = count + 1

set(handles.edit2,'String',count);

end

release(videoSource);

% --- Executes on button press in pushbutton7.

function pushbutton7_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton7 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

close(gcf);

三、运行结果

四、总结

该系统集成了多种经典运动目标检测算法，用户可根据实际场景灵活选择合适的方法进行前景提取。帧差法与三帧差分法计算效率高，适用于简单场景的快速检测；混合高斯模型能够较好地处理光照变化和动态背景，鲁棒性较强；ViBe算法初始化速度快，对背景变化的适应能力良好。界面交互友好，操作流程清晰，支持播放控制与帧数显示，增强了系统的可用性。系统适用于智能视频监控、运动目标跟踪等研究与教学实验场景，后续可进一步引入形态学后处理以优化检测结果，或结合深度学习目标识别算法实现“检测+识别”的一体化分析平台