opencv 学习之 车牌提取

//载入图象 char * path = "d:picture6.jpg"; IplImage * frame = cvLoadImage(path); if(!frame) return 0; cvNamedWindow("frame", 1); cvShowImage("frame", frame);

//均值滤波 cvSmooth(frame, frame, CV_MEDIAN); //cvSmooth(frame, frame, CV_GAUSSIAN, 3, 3); //灰度图 IplImage * gray = cvCreateImage(cvGetSize(frame), frame->depth, 1); cvCvtColor(frame, gray, CV_BGR2GRAY); cvNamedWindow("gray", 1); cvShowImage("gray", gray);

//边沿检测 IplImage * temp = cvCreateImage(cvGetSize(gray), IPL_DEPTH_16S,1); //x方向梯度，垂直边沿 cvSobel(gray, temp, 2, 0, 3); IplImage * sobel = cvCreateImage(cvGetSize(temp), IPL_DEPTH_8U,1); cvConvertScale(temp, sobel, 1, 0); cvNamedWindow("sobel", 1); cvShowImage("sobel", sobel);

//2值化 IplImage * threshold = cvCreateImage(cvGetSize(sobel), gray->depth, 1); cvThreshold(sobel, threshold, 0, 255, CV_THRESH_BINARY|CV_THRESH_OTSU); cvNamedWindow("threshold", 1); cvShowImage("threshold", threshold);

//形态学变化 IplConvKernel * kernal; IplImage * morph = cvCreateImage(cvGetSize(threshold), threshold->depth, 1); //自定义 1x3 的核进行 x 方向的膨胀腐蚀 kernal = cvCreateStructuringElementEx(3, 1, 1, 0, CV_SHAPE_RECT); cvDilate(threshold, morph, kernal, 2); //x 膨胀联通数字 cvErode(morph, morph, kernal, 4); //x 腐蚀去除碎片 cvDilate(morph, morph, kernal, 4); //x 膨胀回复形态 //自定义 3x1 的核进行 y 方向的膨胀腐蚀 kernal = cvCreateStructuringElementEx(1, 3, 0, 1, CV_SHAPE_RECT); cvErode(morph, morph, kernal, 1); //y 腐蚀去除碎片 cvDilate(morph, morph, kernal, 3); //y 膨胀回复形态 cvNamedWindow("erode", 1); cvShowImage("erode", morph);

//轮廓检测 IplImage * frame_draw = cvCreateImage(cvGetSize(frame), frame->depth, frame->nChannels); cvCopy(frame, frame_draw); CvMemStorage * storage = cvCreateMemStorage(0); CvSeq * contour = 0; int count = cvFindContours(morph, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); CvSeq * _contour = contour; for( ; contour != 0; contour = contour->h_next ) { double tmparea = fabs(cvContourArea(contour)); CvRect aRect = cvBoundingRect( contour, 0 ); if(tmparea > ((frame->height*frame->width)/10)) { cvSeqRemove(contour,0); //删除面积小于设定值的轮廓,1/10 continue; } if (aRect.width < (aRect.height*2)) { cvSeqRemove(contour,0); //删除宽高比例小于设定值的轮廓 continue; } if ((aRect.width/aRect.height) > 4 ) { cvSeqRemove(contour,0); //删除宽高比例小于设定值的轮廓 continue; } if((aRect.height * aRect.width) < ((frame->height * frame->width)/100)) { cvSeqRemove(contour,0); //删除宽高比例小于设定值的轮廓 continue; } CvScalar color = CV_RGB( 255, 0, 0); cvDrawContours(frame_draw, contour, color, color, 0, 1, 8 );//绘制外部和内部的轮廓 } cvNamedWindow("轮廓", 1); cvShowImage("轮廓", frame_draw);