车牌识别分两步，一是车牌提取，而是字符识别。
下面是车牌提取。
VS2010。
OpenCV249。
//载入图像char * path = "d:\\picture\\06.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);
//边缘检测IplImage * temp = cvCreateImage(cvGetSize(gray), IPL_DEPTH_16S,1);//x方向梯度，，垂直边缘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);
//二值化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 1×3 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 3×1 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,1/10continue; } 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);
下面就是要字符分割与识别了吧。
在你生活出现失意和疲惫时能给你一点儿力量和希冀,只愿你幸福快乐。
