diff --git a/color_cvt.cpp b/color_cvt.cpp new file mode 100644 index 0000000..95fb291 --- /dev/null +++ b/color_cvt.cpp @@ -0,0 +1,114 @@ +#include "color_cvt.h" + + + +Mat filterbyRGB2(Mat &mat)//可用 +{ + Mat newmat(mat.rows, mat.cols, CV_8UC3); + for( size_t nrow = 0; nrow < mat.rows; nrow++) + { + for(size_t ncol = 0; ncol < mat.cols; ncol++) + { + Vec3i bgr = mat.at(nrow,ncol);//用Vec3b也行 + Vec3i newbgr = newmat.at(nrow,ncol);//用Vec3b也行 + float bgr_sum = (float)bgr.val[0] + (float)bgr.val[1] + (float)bgr.val[2]; + float r = (float)bgr.val[2] / bgr_sum; + float g = (float)bgr.val[1] / bgr_sum; + float b = (float)bgr.val[0] / bgr_sum; + if(((r-g)>0.08 && (r-b)>0.08)) + { + newmat.at(nrow,ncol*newmat.channels()+0) = 255; + newmat.at(nrow,ncol*newmat.channels()+1) = 255; + newmat.at(nrow,ncol*newmat.channels()+2) = 255; + } + else + { + newmat.at(nrow,ncol*newmat.channels()+0) = 0; + newmat.at(nrow,ncol*newmat.channels()+1) = 0; + newmat.at(nrow,ncol*newmat.channels()+2) = 0; + } + } + } + return newmat; +} + + +Mat filterbyHSV(Mat &mat, int color) +{ + Mat newmat(mat.rows, mat.cols, CV_8UC3); + for( size_t nrow = 0; nrow < mat.rows; nrow++) + { + for(size_t ncol = 0; ncol < mat.cols; ncol++) + { + Vec3i hsi = mat.at(nrow,ncol);//用Vec3b也行 + //cout << "(" << hsi.val[0] << "," << hsi.val[1] << "," << hsi.val[2] << ")" << endl; + if((((hsi.val[0] > 0 && hsi.val[0] < 15)||(hsi.val[0] > 155 && hsi.val[0] < 180))) &&//(hsi.val[0] > 0 && hsi.val[0] < 10)||(hsi.val[0] > 100 && hsi.val[0] < 126) + (hsi.val[1] > 43) && + (hsi.val[2] > 46)) + //if((hsi.val[0] > 35 && hsi.val[0] < 77)&& + // (hsi.val[1] > 43 && hsi.val[1] < 255) && + // (hsi.val[2] > 46 && hsi.val[2] < 255)) + { + newmat.at(nrow,ncol*newmat.channels()+0) = 255; + newmat.at(nrow,ncol*newmat.channels()+1) = 255; + newmat.at(nrow,ncol*newmat.channels()+2) = 255; + } + else + { + newmat.at(nrow,ncol*newmat.channels()+0) = 0; + newmat.at(nrow,ncol*newmat.channels()+1) = 0; + newmat.at(nrow,ncol*newmat.channels()+2) = 0; + } + } + } + return newmat; +} + +void RGB2HSV(double red, double green, double blue, double& hue, double& saturation, double& intensity ) +{ + + double r,g,b; + double h,s,i; + + double sum; + double minRGB,maxRGB; + double theta; + + r = red/255.0; + g = green/255.0; + b = blue/255.0; + + minRGB = ((rg)?(r):(g)); + maxRGB = (maxRGB>b)?(maxRGB):(b); + + sum = r+g+b; + i = sum/3.0; + + if( i<0.001 || maxRGB-minRGB<0.001 ) + { + //this is a black image or grayscale image + //in this circumstance, hue is undefined, not zero + h=0.0; + s=0.0; + //return ; + } + else + { + s = 1.0-3.0*minRGB/sum; + theta = sqrt((r-g)*(r-g)+(r-b)*(g-b)); + theta = acos((r-g+r-b)*0.5/theta); + if(b<=g) + h = theta; + else + h = 2*PI - theta; + if(s<=0.01) + h=0; + } + + hue = (int)(h*180/PI); + saturation = (int)(s*100); + intensity = (int)(i*100); +} diff --git a/color_cvt.h b/color_cvt.h new file mode 100644 index 0000000..469ba1a --- /dev/null +++ b/color_cvt.h @@ -0,0 +1,29 @@ +#include +#include +#include +#include +#include "opencv2/core/core.hpp" +#include "highgui.h" +#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/features2d/features2d.hpp" +#include "opencv2/nonfree/nonfree.hpp" +#include +#include +#include +#include +#include +#include +#include +#define PI 3.1415926 + +using namespace std; +using namespace cv; + + +Mat BGR2HSI(Mat &image, Mat &hsi); +Mat filterbyRGB(Mat &mat,int Ra, int Rb,int Ga, int Gb,int Ba, int Bb); +Mat filterbyRGB2(Mat &mat); +Mat filterbyHSI(Mat &mat, int color); +Mat filterbyHSV(Mat &mat, int color); +Mat filterbySVF(Mat &mat); +void RGB2HSV(double red, double green, double blue, double& hue, double& saturation, double& intensity ); \ No newline at end of file diff --git a/main.cpp b/main.cpp new file mode 100644 index 0000000..7dfb01c --- /dev/null +++ b/main.cpp @@ -0,0 +1,147 @@ +#include "color_cvt.h" +#include "pre_img.h" + +RNG rng(12345); +string labelname[500] = {"stop","20t","car forbiden","stop2","5","no noisy","30"}; + +int main() +{ + char path[50]; + //这里载入分类器，方便直接训练 + CvSVM classifier; + classifier.load("model180.txt"); + for(int k = 0;k<100;k++) + { + sprintf(path,"raw/%d.jpg",k+1); + cout << path << endl; + //读取图片 + Mat src = imread(path); + Mat copy; + src.copyTo(copy); + //得到图像参数 + int width = src.cols; //图像宽度 + int height = src.rows; //图像高度 + //色彩分割 + double B=0.0,G=0.0,R=0.0,H=0.0,S=0.0,V=0.0; + Mat Mat_rgb = Mat::zeros( src.size(), CV_8UC1 ); + Mat Mat_rgb_copy;//一个暂存单元 + //Mat copy; + //src.copyTo(copy); + int x,y,px,py; //循环 + for (y=0; y(y,x)[0]; + G = src.at(y,x)[1]; + R = src.at(y,x)[2]; + RGB2HSV(R,G,B,H,S,V); + //红色：337-360 + if((H>=337 && H<=360||H>=0&&H<=10)&&S>=12&&S<=100&&V>20&&V<99) + { + Mat_rgb.at(y,x) = 255; //R + } + } + } + //imshow("hsi",Mat_rgb); + medianBlur(Mat_rgb,Mat_rgb,3); + Mat element = getStructuringElement(MORPH_ELLIPSE, + Size(2*1 + 1, 2*1 + 1), + Point(1,1)); + Mat element1 = getStructuringElement(MORPH_ELLIPSE, + Size(2*3 + 1, 2*3 + 1), + Point(3,3)); + //形态学处理图像，开操作和闭操作，消除噪声，连通有效区域 + erode(Mat_rgb,Mat_rgb,element); + dilate(Mat_rgb,Mat_rgb,element1); + fillHole(Mat_rgb,Mat_rgb); + Mat_rgb.copyTo(Mat_rgb_copy); + /// 多边形逼近轮廓 + 获取矩形和圆形边界框 + //找轮廓 + vector > contours; + vector hierarchy; + findContours( Mat_rgb, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); + /// 多边形逼近轮廓 + 获取矩形和圆形边界框 + vector > contours_poly( contours.size() ); + vector boundRect( contours.size() ); + vectorcenter( contours.size() ); + vectorradius( contours.size() ); + + for( int i = 0; i < contours.size(); i++ ) + { + approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true ); + boundRect[i] = boundingRect( Mat(contours_poly[i]) ); + minEnclosingCircle( contours_poly[i], center[i], radius[i] ); + } + /// 画多边形轮廓 + 包围的矩形框 + 圆形框 + Mat drawing = Mat::zeros( Mat_rgb.size(), CV_8UC3 ); + int count1 = 0; + for( int i = 0; i< contours.size(); i++ ) + { + Rect rect = boundRect[i]; + //首先进行一定的限制，筛选出区域 + //高宽比限制 + float ratio = (float)rect.width / (float)rect.height; + //轮廓面积 + float Area = (float)rect.width * (float)rect.height; + float dConArea = (float)contourArea(contours[i]); + float dConLen = (float)arcLength(contours[i],1); + if(dConArea <400) + continue; + if(ratio>2||ratio<0.5) + continue; + + //进行圆筛选，通过四块的缺失像素比较 + Mat roiImage; + Mat_rgb_copy(rect).copyTo(roiImage); + //imshow("test",roiImage); + Mat temp; + copy(rect).copyTo(temp); + //imshow("test2",temp); + bool iscircle = isCircle(roiImage,temp); + cout << "circle:" << iscircle << endl; + if(!iscircle) + continue; + //接下来是形状限制！这里检测圆形标志牌 + float C = (4*PI*dConArea)/(dConLen*dConLen); + if(C < 0.4)//利用圆度初步对形状进行筛选 + continue; + //cout << C << "," << R << "," << E << "," << E << endl; + copy(rect).copyTo(roiImage); + //imshow("roi",roiImage); + //count1++; + //sprintf(path,"newresult1/%d_%d.jpg",k,count1); + //imwrite(path, temp); + //sprintf(path,"newresult2/%d.jpg",count1); + //imwrite(path, roiImage); + //*********svm********* + //imshow("a",temp); + Mat temp2 = Mat::zeros( temp.size(), CV_8UC1 ); + cvtColor(temp,temp2,CV_BGR2GRAY); + resize(temp2,temp2,Size(45,45)); + //threshold(temp2,temp2,120,255,THRESH_BINARY_INV); + temp2 = temp2.reshape(0,1); + temp2.convertTo(temp2, CV_32F); + int result = (int)classifier.predict(temp2)-1;//svm预测 + //********************* + Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) ); + drawContours( drawing, contours_poly, i, color, 1, 8, vector(), 0, Point() ); + rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0 ); + rectangle( src, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0 ); + putText(src, labelname[result], cvPoint(boundRect[i].x, boundRect[i].y-10),1,1,CV_RGB(255, 0, 0),2);//红色字体注释 + //circle( drawing, center[i], (int)radius[i], color, 2, 8, 0 ); + count1++; + sprintf(path,"result/%d_%d.jpg",k,count1); + imwrite(path, src);//保存最终的检测识别结果 + } + + //结果显示 + //imshow("src",src); + //imshow("drawing",drawing); + //imshow("filter", Mat_rgb); + //waitKey(0); + } + waitKey(0); + return 0; +} \ No newline at end of file diff --git a/model180.txt b/model180.txt new file mode 100644 index 0000000..117c17d --- /dev/null +++ b/model180.txt @@ -0,0 +1,6331 @@ +%YAML:1.0 +my_svm: !!opencv-ml-svm + svm_type: C_SVC + kernel: { type:LINEAR } + C: 100. + term_criteria: { epsilon:2.2204460492503131e-016, iterations:1000 } + var_all: 2025 + var_count: 2025 + class_count: 5 + class_labels: !!opencv-matrix + rows: 1 + cols: 5 + dt: i + data: [ 1, 2, 3, 4, 5 ] + sv_total: 10 + support_vectors: + - [ -2.43128710e-007, 0., 0., 0., 0., 0., -2.43128710e-007, 0., 0., + -2.43128710e-007, -2.43128710e-007, 2.43128710e-007, + -2.43128710e-007, 0., -9.72514840e-007, -1.33720787e-005, + -1.36152066e-005, -1.36152066e-005, -1.21564347e-006, + 4.13318776e-006, 8.02324666e-006, 1.41014643e-005, + 1.48308509e-005, 1.38583355e-005, 1.43445932e-005, + 8.26637552e-006, 2.67441555e-006, -4.61944546e-006, + -5.59195996e-006, -1.72621367e-005, -4.86257420e-007, 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index: [ 7 ] + - + sv_count: 1 + rho: -2.3796368935637577e+000 + alpha: [ 1. ] + index: [ 8 ] + - + sv_count: 1 + rho: -2.1845679943209753e+000 + alpha: [ 1. ] + index: [ 9 ] diff --git a/pre_img.cpp b/pre_img.cpp new file mode 100644 index 0000000..a963cb8 --- /dev/null +++ b/pre_img.cpp @@ -0,0 +1,115 @@ +#include "pre_img.h" + + +void fillHole(const Mat srcBw, Mat &dstBw) +{ + Size m_Size = srcBw.size(); + Mat Temp=Mat::zeros(m_Size.height+2,m_Size.width+2,srcBw.type());//延展图像 + srcBw.copyTo(Temp(Range(1, m_Size.height + 1), Range(1, m_Size.width + 1))); + + cv::floodFill(Temp, Point(0, 0), Scalar(255));//填充区域 + + Mat cutImg;//裁剪延展的图像 + Temp(Range(1, m_Size.height + 1), Range(1, m_Size.width + 1)).copyTo(cutImg); + + dstBw = srcBw | (~cutImg); +} + +bool isCircle(const Mat srcBw,Mat& mytemp)//（待改进） +{//输入的是一个灰度图像 + Mat temp = Mat::zeros( srcBw.size(), CV_8UC1 ); + bool iscircle = false; + //获得srcBw信息 + int w = srcBw.cols; + int h = srcBw.rows; + int w1 = mytemp.cols; + int h1 = mytemp.rows; + //cout << w << " " << w1 << " " << h << " " << h1 << endl; + int count1=0;//各部分的缺失像素计数器 + int count2=0; + int count3=0; + int count4=0; + //将srcBw平均分成四份,进行访问缺失的像素个数、所占比重 + //先访问左上 + for(int i = 0;i < h/2;i ++) + { + for(int j = 0;j < w/2;j ++) + { + if(srcBw.at(i,j) == 0) + { + temp.at(i,j) = 255; + mytemp.at(i,j*mytemp.channels()+0) = 255; + mytemp.at(i,j*mytemp.channels()+1) = 255; + mytemp.at(i,j*mytemp.channels()+2) = 255; + count1 ++; + } + } + } + //右上 + for(int i = 0;i < h/2;i ++) + { + for(int j = w/2-1;j < w;j ++) + { + if(srcBw.at(i,j) == 0) + { + temp.at(i,j) = 255; + mytemp.at(i,j*mytemp.channels()+0) = 255; + mytemp.at(i,j*mytemp.channels()+1) = 255; + mytemp.at(i,j*mytemp.channels()+2) = 255; + count2 ++; + } + } + } + //左下 + for(int i = h/2-1;i < h;i ++) + { + for(int j = 0;j < w/2;j ++) + { + if(srcBw.at(i,j) == 0) + { + temp.at(i,j) = 255; + mytemp.at(i,j*mytemp.channels()+0) = 255; + mytemp.at(i,j*mytemp.channels()+1) = 255; + mytemp.at(i,j*mytemp.channels()+2) = 255; + count3 ++; + } + } + } + //右下 + for(int i = h/2-1;i < h;i ++) + { + for(int j = w/2-1;j < w;j ++) + { + if(srcBw.at(i,j) == 0) + { + temp.at(i,j) = 255; + mytemp.at(i,j*mytemp.channels()+0) = 255; + mytemp.at(i,j*mytemp.channels()+1) = 255; + mytemp.at(i,j*mytemp.channels()+2) = 255; + count4 ++; + } + } + } + + + float c1 = (float)count1/(float)(w*h);//左上 + float c2 = (float)count2/(float)(w*h);//右上 + float c3 = (float)count3/(float)(w*h);//左下 + float c4 = (float)count4/(float)(w*h);//右下 + //imshow("temp",mytemp); + cout << "result: " << c1 << "," << c2 + << "," << c3 << "," << c4 << endl; + + //限定每个比率的范围 + if((c1>0.037&&c1<0.12)&&(c2>0.037&&c2<0.12)&&(c2>0.037&&c2<0.12)&&(c2>0.037&&c2<0.12)) + { + //限制差值,差值比较容错，相邻块之间差值相近，如左上=右上&&左下=右下或左上=左下&&右上=右下 + if((abs(c1-c2)<0.04&&abs(c3-c4)<0.04)||(abs(c1-c3)<0.04&&abs(c2-c4)<0.04)) + { + iscircle = true; + } + } + + + return iscircle; +} \ No newline at end of file diff --git a/pre_img.h b/pre_img.h new file mode 100644 index 0000000..ae9183b --- /dev/null +++ b/pre_img.h @@ -0,0 +1,5 @@ +#include"color_cvt.h" + + +void fillHole(const Mat srcBw, Mat &dstBw);//填充圆环 +bool isCircle(const Mat srcBw, Mat& mytemp);//二次判断是否是圆形（圆形在矩形框内，则四个角会缺失，缺失面积应该相近） \ No newline at end of file diff --git a/raw/1.jpg b/raw/1.jpg new file mode 100644 index 0000000..3741692 Binary files /dev/null and b/raw/1.jpg differ diff --git a/raw/10.jpg b/raw/10.jpg new file mode 100644 index 0000000..a0bd3b2 Binary files /dev/null and b/raw/10.jpg differ diff --git a/raw/100.jpg b/raw/100.jpg new file mode 100644 index 0000000..777439a Binary files /dev/null and b/raw/100.jpg differ diff --git a/raw/101.jpg b/raw/101.jpg new file mode 100644 index 0000000..e68966b Binary files /dev/null and b/raw/101.jpg differ diff --git a/raw/102.jpg b/raw/102.jpg new file mode 100644 index 0000000..f37492a Binary files /dev/null and b/raw/102.jpg differ diff --git a/raw/103.jpg b/raw/103.jpg new file mode 100644 index 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