※ 引述《SUPERERIC (@_@)》之铭言： : 现在正用OpenCV 写影像辨识,参考OpenCV中文网站 : http://www.opencv.org.cn/index.php/Cv%E5%9B%BE%E5%83%8F%E5%A4%84%E7%90%86#Smooth : 看了些资料,都说到第一步要平滑化(smooth) : 在OpenCV中文网站提到的OpenCV : 那里虽然提到基本语法,但没有范例 : 请问有Visual C++ OpenCV 平滑化的范例吗? : 而且我要做的是影片辨识,不知道处理法跟静态辨识差异在哪? 现在我找到一系列:二值化、灰阶化、取背、取轮廓图像的程式 http://ppt.cc/m5hr 我是利用Visual C++ 配合OpenCV 现在我想要输入一个"动态影像"去做辨识 请问我该从何下手(我想要一秒大概抓30个图片) 我想问: 1.如何抓到档案 2.如何建立记忆体空间 3.抓到我想要颜色、轮廓 以下是程式(我用一个button触发) 抱歉!可能阅读困难,不好意思,稍後附上排版好的原档 #pragma once #include "stdafx.h"#include <stdlib.h>#include <math.h>#include <string>#include <stdio.h>#include <cv.h>#include <highgui.h>#include <direct.h> CvCapture *open_webcam; IplImage *webcam; IplImage *open_Image; int argc; char* argv[50]; IplImage *src = 0; //定义源图像指针 IplImage *tmp = 0; //定义临时图像指针 IplImage *src_back = 0; //定义源图像背景指针 IplImage *dst_gray = 0; //定义源文件去掉背景後的目标灰度图像指针 IplImage *dst_bw = 0; //定义源文件去掉背景後的目标二值图像指针 IplImage *dst_contours = 0; //定义轮廓图像指针 IplConvKernel *element = 0; //定义形态学结构指针 int Number_Object =0; //定义目标对象数量 int contour_area_tmp = 0; //定义目标对象面积临时寄存器 int contour_area_sum = 0; //定义目标所有对象面积的和 int contour_area_ave = 0; //定义目标对象面积平均值 int contour_area_max = 0; //定义目标对象面积最大值 CvMemStorage *stor = 0; CvSeq * cont = 0; CvContourScanner contour_scanner; CvSeq * a_contour= 0; namespace OPENCV { using namespace System; using namespace System::ComponentModel; using namespace System::Collections; using namespace System::Windows::Forms; using namespace System::Data; using namespace System::Drawing; /// <summary> /// Form1 的摘要 /// /// 警告: 如果您变更这个类别的名称，就必须变更与这个类别所依据之所有 .resx 档 案关联的 /// Managed 资源编译器工具的 'Resource File Name' 属性。 /// 否则，这些设计工具 /// 将无法与这个表单关联的当地语系化资源 /// 正确互动。 /// </summary> public ref class Form1 : public System::Windows::Forms::Form { public: Form1(void) { InitializeComponent(); // //TODO: 在此加入建构函式程式码 // } protected: /// <summary> /// 清除任何使用中的资源。 /// </summary> ~Form1() { if (components) { delete components; } } private: System::Windows::Forms::Button^ button1; private: System::Windows::Forms::Button^ button2; private: System::Windows::Forms::Button^ button3; protected: private: /// <summary> /// 设计工具所需的变数。 /// </summary> System::ComponentModel::Container ^components; #pragma region Windows Form Designer generated code /// <summary> /// 此为设计工具支援所需的方法 - 请勿使用程式码编辑器修改这个方法的内容。 /// /// </summary> void InitializeComponent(void) { this->button1 = (gcnew System::Windows::Forms::Button()); this->button2 = (gcnew System::Windows::Forms::Button()); this->button3 = (gcnew System::Windows::Forms::Button()); this->SuspendLayout(); // // button1 // this->button1->Location = System::Drawing::Point(12, 182); this->button1->Name = L"button1"; this->button1->Size = System::Drawing::Size(84, 23); this->button1->TabIndex = 0; this->button1->Text = L"open_webcam"; this->button1->UseVisualStyleBackColor = true; this->button1->Click += gcnew System::EventHandler(this, &Form1::button1_Click); // // button2 // this->button2->Location = System::Drawing::Point(188, 182); this->button2->Name = L"button2"; this->button2->Size = System::Drawing::Size(84, 23); this->button2->TabIndex = 1; this->button2->Text = L"showpicture"; this->button2->UseVisualStyleBackColor = true; this->button2->Click += gcnew System::EventHandler(this, &Form1::button2_Click); // // button3 // this->button3->Location = System::Drawing::Point(112, 143); this->button3->Name = L"button3"; this->button3->Size = System::Drawing::Size(75, 23); this->button3->TabIndex = 2; this->button3->Text = L"show1"; this->button3->UseVisualStyleBackColor = true; this->button3->Click += gcnew System::EventHandler(this, &Form1::button3_Click); // // Form1 // this->AutoScaleDimensions = System::Drawing::SizeF(6, 12); this->AutoScaleMode = System::Windows::Forms::AutoScaleMode::Font; this->ClientSize = System::Drawing::Size(284, 262); this->Controls->Add(this->button3); this->Controls->Add(this->button2); this->Controls->Add(this->button1); this->Name = L"Form1"; this->Text = L"Form1"; this->Load += gcnew System::EventHandler(this, &Form1::Form1_Load); this->ResumeLayout(false); } #pragma endregion private: System::Void Form1_Load(System::Object^ sender, System::EventArgs^ e) { } private: System::Void button1_Click(System::Object^ sender, System::EventArgs^ e) { //************************************************// // Open Camera // open_webcam =cvCaptureFromCAM(0); cvNamedWindow("open_webcam",1); while(1) { webcam = cvQueryFrame(open_webcam); cvShowImage("open_webcam",webcam); if(cvWaitKey(10)>=0) { break; } } cvReleaseCapture(&open_webcam); cvDestroyWindow("open_webcam"); } private: System::Void button2_Click(System::Object^ sender, System::EventArgs^ e) { //************************************************// // Open Image // open_Image = cvLoadImage("lenna_256.bmp",1); cvNamedWindow("showpicture", 0); while(1) { cvShowImage("showpicture", open_Image); if(cvWaitKey(10)>=0) { break; } } cvDestroyWindow("showpicture"); } private: System::Void button3_Click(System::Object^ sender, System::EventArgs^ e) { //1.读取和显示图像 /* the first command line parameter must be image file name */ if ( argc == 2 && (src = cvLoadImage(argv[1], 0))!=0 ) { ; } else { src = cvLoadImage("rice.jpg", 0); } cvNamedWindow( "src", CV_WINDOW_AUTOSIZE ); cvShowImage( "src", src ); //cvSmooth(src, src, CV_MEDIAN, 3, 0, 0, 0); //中值滤波，消除小的杂讯； //2.估计图像背景 tmp = cvCreateImage( cvGetSize(src), src->depth, src->nChannels); src_back = cvCreateImage( cvGetSize(src), src->depth, src->nChannels); //创建结构元素 element = cvCreateStructuringElementEx( 4, 4, 1, 1, CV_SHAPE_ELLIPSE, 0); //用该结构对源图象进行数学形态学的开操作後，估计背景亮度 cvErode( src, tmp, element, 10); cvDilate( tmp, src_back, element, 10); cvNamedWindow( "src_back", CV_WINDOW_AUTOSIZE ); cvShowImage( "src_back", src_back ); //3.从源图象中减区背景图像 dst_gray = cvCreateImage( cvGetSize(src), src->depth, src->nChannels); cvSub( src, src_back, dst_gray, 0); cvNamedWindow( "dst_gray", CV_WINDOW_AUTOSIZE ); cvShowImage( "dst_gray", dst_gray ); //4.使用阈值操作将图像转换为二值图像 dst_bw = cvCreateImage( cvGetSize(src), src->depth, src->nChannels); cvThreshold( dst_gray, dst_bw ,50, 255, CV_THRESH_BINARY ); //取阈值为50把 图像转为二值图像 //cvAdaptiveThreshold( dst_gray, dst_bw, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, 3, 5 ); cvNamedWindow( "dst_bw", CV_WINDOW_AUTOSIZE ); cvShowImage( "dst_bw", dst_bw ); //5.检查图像中的目标对象数量 stor = cvCreateMemStorage(0); cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint), stor); Number_Object = cvFindContours( dst_bw, stor, &cont, sizeof(CvContour), CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) ); //找到所有轮廓 printf("Number_Object: %d\n", Number_Object); //6.计算图像中对象的统计属性 dst_contours = cvCreateImage( cvGetSize(src), src->depth, src->nChannels); cvThreshold( dst_contours, dst_contours ,0, 255, CV_THRESH_BINARY); //在画 轮廓前先把图像变成白色 for(;cont;cont = cont->h_next) { cvDrawContours( dst_contours, cont, CV_RGB(255, 0, 0), CV_RGB(255, 0, 0), 0, 1, 8, cvPoint(0, 0) ); //绘制当前轮廓 contour_area_tmp = fabs(cvContourArea( cont, CV_WHOLE_SEQ )); //获取当 前轮廓面积 if( contour_area_tmp > contour_area_max ) { contour_area_max = contour_area_tmp; //找到面积最大的轮廓 } contour_area_sum += contour_area_tmp; //求所有轮廓的面积和 } contour_area_ave = contour_area_sum/ Number_Object; //求出所有轮廓的平均值 printf("contour_area_ave: %d\n", contour_area_ave ); printf("contour_area_max: %d\n", contour_area_max ); cvNamedWindow( "dst_contours", CV_WINDOW_AUTOSIZE ); cvShowImage( "dst_contours", dst_contours ); cvWaitKey(-1); //等待退出 cvReleaseImage(&src); cvReleaseImage(&tmp); cvReleaseImage(&src_back); cvReleaseImage(&dst_gray); cvReleaseImage(&dst_bw); cvReleaseImage(&dst_contours); cvReleaseMemStorage(&stor); cvDestroyWindow( "src" ); cvDestroyWindow( "src_back" ); cvDestroyWindow( "dst_gray" ); cvDestroyWindow( "dst_bw" ); cvDestroyWindow( "dst_contours" ); //void cvDestroyAllWindows(void); //return 0; } }; } -- -- ㄧ○︿ \ √ ﹀.......GO!GO!GO! --

※ 发信站: 批踢踢实业坊(ptt.cc) ◆ From: 120.96.45.46 ※ 编辑: SUPERERIC 来自: 120.96.45.46 (07/20 15:20) ※ 编辑: SUPERERIC 来自: 120.96.45.46 (07/20 15:21)