OpenCV依据颜色的车牌定位

OpenCV依据颜色的车牌定位

http://blog.csdn.net/superdont/article/details/24936341

OpenCV依据颜色的车牌定位

2014-05-03 22:05 4626人阅读 评论(3) 收藏 举报

 分类：

 

图像处理（91）  opencv（24） 

版权声明：本文为博主原创文章，未经博主允许不得转载。

 

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);

效果如下：

 

 

 

颜色可以考虑更细致，或者考虑在其他颜色空间内实现。