简单的集装箱号码识别

2017-5-31：花了一个礼拜的时间，通过网上各种找资料，自己独自完成了一个简单的集装箱号码识别的小程序；

网上大多资料都是车牌号码识别，集装箱号码可能所处的环境因素会复杂一点，比如号码横竖问题、拍摄角度不同、号码字体不同...但总体框架还是和车牌识别一个道理的；能力有限很多因素都没考虑进来，暑假有机会的话希望能进一步研究一下，这先做个小小总结以防时间久了想复习一下都不知道从哪抓起；

1 获取号码区域

集装箱号码类似与文字区域的检测，先使用 morphologyEx函数膨胀，再用 cvFindContours 函数提取轮廓；

集装箱号码的排列一般分横型和竖型，所以膨胀处理也对应两种

// 寻找所有矩形轮廓// 参数:     // 1. pBinary: 输入二值图像，单通道，位深IPL_DEPTH_8U。    // 2. Size s: 横竖形态选择参数vector FindRect(IplImage *src_img, Size s){vector Rectbuf;IplImage *gray_img = cvCreateImage(cvGetSize(src_img), 8, 1);cvSmooth(src_img, src_img, CV_GAUSSIAN);//IplI *arr转mat：mat(arr)cvCvtColor(src_img, gray_img, CV_BGR2GRAY);double th_maxArea = (gray_img->width*gray_img->height)*0.5;double th_minArea = (gray_img->width*gray_img->height)*0.01;double th_maxRatio = 0.3;//height/width比double th_minRatio = 0.01;Mat element1 = getStructuringElement(MORPH_RECT, s);//morphologyEx(cvarrToMat(gray_img), cvarrToMat(gray_img), MORPH_CLOSE, element1);morphologyEx(cvarrToMat(gray_img), cvarrToMat(gray_img), MORPH_DILATE, element1);IplImage *pBinary = cvCreateImage(cvGetSize(gray_img), 8, 1);int thresh = Otsu(gray_img);cvThreshold(gray_img, pBinary, thresh, 255, CV_THRESH_BINARY);//cvAdaptiveThreshold(gray_img, pBinary, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, 5, 5);CvSeq *pContour = NULL;CvMemStorage *pStorage = NULL;//IplImage *dst = cvCreateImage(cvGetSize(gray_img), 8, 3);// 执行条件     if (pBinary){// 查找所有轮廓     pStorage = cvCreateMemStorage(0);cvFindContours(pBinary, pStorage, &pContour, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE); int cnt = 0;CvContourScanner scanner = cvStartFindContours(pBinary, pStorage);while (pContour = cvFindNextContour(scanner)){//double tmparea = fabs(cvContourArea(pContour));CvRect rect = cvBoundingRect(pContour, 0);double tmparea = rect.height*rect.width;//面积筛选if (tmparea < th_minArea || tmparea > th_maxArea){cvSubstituteContour(scanner, NULL);//删除当前的轮廓  continue;}double tmpRatio = (rect.height th_maxRatio)//长宽比筛选{cvSubstituteContour(scanner, NULL);//删除当前的轮廓  continue;}cnt++;Rectbuf.push_back(rect);//cvDrawContours(src_img, pContour, CV_RGB(0, 0, 255), CV_RGB(0, 0, 255), 0, 2, CV_FILLED, cvPoint(0, 0));cvRectangle(src_img, cvPoint(rect.x, rect.y), cvPoint(rect.x + rect.width, rect.y + rect.height), CV_RGB(255, 0, 0), 1, 8, 0);}pContour = cvEndFindContours(&scanner);cout << Rectbuf.size() << endl;cvReleaseMemStorage(&pStorage);pStorage = NULL;}cvNamedWindow("result");cvShowImage("result", src_img); waitKey();destroyWindow("result");cvReleaseImage(&pBinary);cvReleaseImage(&gray_img);return Rectbuf;}

2 确定单个字符

3 识别字符