使用颜色属性:
Mat srcImage=imread("image/t10.jpg"); Mat srcShowImage; srcImage.copyTo(srcShowImage); //imshow("a",srcImage); int i,j; int cPointB,cPointG,cPointR; for(i=1;i<srcImage.rows;i++) for(j=1;j<srcImage.cols;j++) { cPointB=srcImage.at<Vec3b>(i,j)[0]; cPointG=srcImage.at<Vec3b>(i,j)[1]; cPointR=srcImage.at<Vec3b>(i,j)[2]; if(cPointB>80&cPointR<80&cPointG<80) //提取蓝色,将该区域设置为黑色 { srcImage.at<Vec3b>(i,j)[0]=0; srcImage.at<Vec3b>(i,j)[1]=0; srcImage.at<Vec3b>(i,j)[2]=0; } else if(cPointB>200&cPointR>200&cPointG>200) //提取白色,将其设置为黑色 { srcImage.at<Vec3b>(i,j)[0]=0; srcImage.at<Vec3b>(i,j)[1]=0; srcImage.at<Vec3b>(i,j)[2]=0; } else { srcImage.at<Vec3b>(i,j)[0]=255; srcImage.at<Vec3b>(i,j)[1]=255; srcImage.at<Vec3b>(i,j)[2]=255; } } cvtColor(srcImage,srcImage, CV_BGR2GRAY); threshold(srcImage,srcImage,127, 255,CV_THRESH_BINARY); //使用差分法,去掉不相关的区域。 for(i=1;i<srcImage.rows;i++) for(j=1;j<srcImage.cols-1;j++) { srcImage.at<uchar>(i,j)=srcImage.at<uchar>(i,j+1)-srcImage.at<uchar>(i,j); } threshold(srcImage,srcImage,127, 255,CV_THRESH_BINARY_INV);//通过二值化的方式来取反。 //erode(srcImage,srcImage,Mat(5,5,CV_8U),Point(-1,-1),2); //腐蚀 // dilate(src,src,Mat(5,5,CV_8U),Point(-1,-1),2); //膨胀 // morphologyEx(src,src,MORPH_OPEN,Mat(3,3,CV_8U),Point(-1,-1),1); //开运算 // morphologyEx(src,src,MORPH_CLOSE,Mat(3,3,CV_8U),Point(-1,-1),1); //闭运算 erode(srcImage,srcImage,Mat(3,3,CV_8U),Point(-1,-1),5); threshold(srcImage,srcImage,127,255,CV_THRESH_BINARY_INV); imshow("a",srcImage); vector<vector<Point> > contours; vector<Vec4i> hierarchy; findContours(srcImage, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) ); for( int i = 0; i < contours.size(); i++ ) { //使用边界框的方式 CvRect aRect = boundingRect(contours[i]); int tmparea=aRect.height*aRect.height; if (((double)aRect.width/(double)aRect.height>2)&& ((double)aRect.width/(double)aRect.height<6)&& tmparea>=2000&&tmparea<=25000) { rectangle(srcShowImage,cvPoint(aRect.x,aRect.y),cvPoint(aRect.x+aRect.width ,aRect.y+aRect.height),color,2); //cvDrawContours( dst, contours, color, color, -1, 1, 8 ); } } imshow("da",srcShowImage);
颜色可以考虑更细致,或者考虑在其他颜色空间内实现。
OpenCV依据颜色的车牌定位,布布扣,bubuko.com
原文:http://blog.csdn.net/superdont/article/details/24936341