欢迎来到海神之光博客之家✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab图像处理仿真内容点击①Matlab图像处理进阶版②付费专栏Matlab图像处理初级版⛳️关注CSDN海神之光更多资源等你来⛄一、火灾检测简介1 案例背景接触式火灾探测器对环境有一定要求,且常适用于室内空间。目前,利用视频图像与计算机视觉技术相结合,进行火灾的检测和常规探查成为本领域的研究新方向。针对烟雾区域稀疏、扩散缓慢的特征,现有算法提取疑似烟雾区域不完整的问题,该文提出一种动态多帧差分法。首先,对视频图像序列进行非线性滤波,抑制一定的噪声;然后,根据面积比率动态提取疑似烟雾区域;最后,根据面积与周长变化确定烟区。通过多个维度对实验结果进行综合分析,表明该方法较为优秀,且对不同条件下的烟雾图像特征提取方法的选取有指导意义。2 动态多帧差法算法流程本研究改进的算法主要有3个步骤步骤1提取视频序列帧图像对图像进行滤波处理提高图像清晰度降低噪声的影响再进行形态学处理。步骤2对图像进行帧差操作获取到的连续帧的运动目标求面积且对连续面积结果作比根据比例数值为阈值来选取合适的帧间隔数作差分。步骤3对得到的结果进行形态学操作与轮廓提取得到结果。通过以上3个步骤后可得到较为合适的运动前景。算法的烟雾检测流程如图1所示。图1 烟雾检测流程该算法整体流程共包含4个模块(1预处理利用中值滤波去除原始视频中的噪声为提高特征提取效果做准备。(2疑似烟雾确定使用以面积比率为阈值的动态多帧差法获取疑似烟雾。(3特征提取再提取疑似烟区的面积、周长。(4确定烟区根据提取的疑似烟区的面积与周长变化来综合判别此区域是否为烟雾区域。⛄二、部分源代码function varargout zznb(varargin)% ZZNB MATLAB code for zznb.fig% ZZNB, by itself, creates a new ZZNB or raises the existing% singleton*.%% H ZZNB returns the handle to a new ZZNB or the handle to% the existing singleton*.%% ZZNB(‘CALLBACK’,hObject,eventData,handles,…) calls the local% function named CALLBACK in ZZNB.M with the given input arguments.%% ZZNB(‘Property’,‘Value’,…) creates a new ZZNB or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before zznb_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to zznb_OpeningFcn via varargin.%% *See GUI Options on GUIDE’s Tools menu. Choose “GUI allows only one% instance to run (singleton)”.%% See also: GUIDE, GUIDATA, GUIHANDLES% Edit the above text to modify the response to help zznb% Last Modified by GUIDE v2.5 06-Jun-2020 11:14:09% Begin initialization code - DO NOT EDITgui_Singleton 1;gui_State struct(‘gui_Name’, mfilename, …‘gui_Singleton’, gui_Singleton, …‘gui_OpeningFcn’, zznb_OpeningFcn, …‘gui_OutputFcn’, zznb_OutputFcn, …‘gui_LayoutFcn’, [] , …‘gui_Callback’, []);if nargin ischar(varargin{1})gui_State.gui_Callback str2func(varargin{1});endif nargout[varargout{1:nargout}] gui_mainfcn(gui_State, varargin{:});elsegui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% — Executes just before zznb is made visible.function zznb_OpeningFcn(hObject, eventdata, handles, varargin)% This function has no output args, see OutputFcn.% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% varargin command line arguments to zznb (see VARARGIN)% Choose default command line output for zznbhandles.output hObject;% Update handles structureguidata(hObject, handles);% UIWAIT makes zznb wait for user response (see UIRESUME)% uiwait(handles.figure1);% — Outputs from this function are returned to the command line.function varargout zznb_OutputFcn(hObject, eventdata, handles)% varargout cell array for returning output args (see VARARGOUT);% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Get default command line output from handles structurevarargout{1} handles.output;function edit1_CreateFcn(hObject, eventdata, handles)% hObject handle to edit1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))set(hObject,‘BackgroundColor’,‘white’);end% — Executes during object creation, after setting all properties.function edit2_CreateFcn(hObject, eventdata, handles)% hObject handle to edit2 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))set(hObject,‘BackgroundColor’,‘white’);endfunction edit3_Callback(hObject, eventdata, handles)% hObject handle to edit3 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Hints: get(hObject,‘String’) returns contents of edit3 as text% str2double(get(hObject,‘String’)) returns contents of edit3 as a double% — Executes during object creation, after setting all properties.function edit3_CreateFcn(hObject, eventdata, handles)% hObject handle to edit3 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))set(hObject,‘BackgroundColor’,‘white’);end% — Executes on button press in pushbutton1.function pushbutton1_Callback(hObject, eventdata, handles)% hObject handle to pushbutton1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)obj VideoReader(uigetfile(‘*.mp4’,‘选择视频’));%输入视频位置setappdata(0,‘obj’,obj);%设置全局变量Show_Framesread(obj,1);%显示第一帧作为封面axes(handles.axes1);imshow(Show_Frames);set(handles.text16,‘String’,‘视频待识别…请稍等’);⛄三、运行结果⛄四、matlab版本及参考文献1 matlab版本2014a2 参考文献[1] 蔡利梅.MATLAB图像处理——理论、算法与实例分析[M].清华大学出版社2020.3 备注简介此部分摘自互联网仅供参考若侵权联系删除 仿真咨询1 各类智能优化算法改进及应用生产调度、经济调度、装配线调度、充电优化、车间调度、发车优化、水库调度、三维装箱、物流选址、货位优化、公交排班优化、充电桩布局优化、车间布局优化、集装箱船配载优化、水泵组合优化、解医疗资源分配优化、设施布局优化、可视域基站和无人机选址优化2 机器学习和深度学习方面卷积神经网络CNN、LSTM、支持向量机SVM、最小二乘支持向量机LSSVM、极限学习机ELM、核极限学习机KELM、BP、RBF、宽度学习、DBN、RF、RBF、DELM、XGBOOST、TCN实现风电预测、光伏预测、电池寿命预测、辐射源识别、交通流预测、负荷预测、股价预测、PM2.5浓度预测、电池健康状态预测、水体光学参数反演、NLOS信号识别、地铁停车精准预测、变压器故障诊断3 图像处理方面图像识别、图像分割、图像检测、图像隐藏、图像配准、图像拼接、图像融合、图像增强、图像压缩感知4 路径规划方面旅行商问题TSP、车辆路径问题VRP、MVRP、CVRP、VRPTW等、无人机三维路径规划、无人机协同、无人机编队、机器人路径规划、栅格地图路径规划、多式联运运输问题、车辆协同无人机路径规划、天线线性阵列分布优化、车间布局优化5 无人机应用方面无人机路径规划、无人机控制、无人机编队、无人机协同、无人机任务分配6 无线传感器定位及布局方面传感器部署优化、通信协议优化、路由优化、目标定位优化、Dv-Hop定位优化、Leach协议优化、WSN覆盖优化、组播优化、RSSI定位优化7 信号处理方面信号识别、信号加密、信号去噪、信号增强、雷达信号处理、信号水印嵌入提取、肌电信号、脑电信号、信号配时优化8 电力系统方面微电网优化、无功优化、配电网重构、储能配置9 元胞自动机方面交通流 人群疏散 病毒扩散 晶体生长10 雷达方面卡尔曼滤波跟踪、航迹关联、航迹融合