C++/OpenCV2.4.xx印刷数字精确识别源码

/***************************************************** 图片数字识别 *****************************************************/ #include "cv.h" #include "highgui.h" #include "cxcore.h" #include<windows.h> #include<iostream> using namespace std; using namespace cv; int getColSum(Mat src, int col); //列求和 int cutLeft(Mat& src, Mat& leftImg, Mat& rightImg);//左右切割 void cutTop(Mat& src, Mat& dstImg);//上下切割 int getRowSum(Mat src, int row); //航求和 void getPXSum(Mat &src, int &a);//获取所有像素点和 int getSubtract(Mat &src, int TemplateNum); void pictureCut(); //模板数字图片切割 LPCWSTR dirName = L".\\AAA"; //保存分割后照片的文件夹 int main() { pictureCut(); //创建文件夹保存分割后的照片 BOOL flag = CreateDirectory(dirName, NULL); Mat src = imread(".\\sss.png", CV_LOAD_IMAGE_GRAYSCALE); threshold(src, src, 100, 255, CV_THRESH_BINARY_INV); imshow("原始灰度图二值处理后", src); printf("识别的数字是：\n"); Mat leftImg, rightImg; int res = cutLeft(src, leftImg, rightImg); int i = 0; while (res == 0) { char nameLeft[10]; sprintf(nameLeft, "%dLeft", i); Mat srcTmp = rightImg; getSubtract(leftImg, 10);//数字识别 res = cutLeft(srcTmp, leftImg, rightImg); } waitKey(0); return 0; } //模板数字图片切割 void pictureCut() { Mat src = imread(".\\base.png", CV_LOAD_IMAGE_GRAYSCALE); threshold(src, src, 100, 255, CV_THRESH_BINARY_INV); Mat leftImg, rightImg; int res = cutLeft(src, leftImg, rightImg); int i = 0; while (res == 0) { char nameLeft[10]; sprintf(nameLeft, "%dLeft", i); char nameRight[10]; sprintf(nameRight, "%dRight", i); i++; stringstream ss; ss << nameLeft; imwrite(".\\AAA\\" + ss.str() + ".jpg", leftImg);//保存截取图片做为模板 ss >> nameLeft; Mat srcTmp = rightImg; res = cutLeft(srcTmp, leftImg, rightImg); } } int cutLeft(Mat& src, Mat& leftImg, Mat& rightImg)//左右切割 { int left, right; left = 0; right = src.cols; int i; for (i = 0; i < src.cols; i++) { int colValue = getColSum(src, i); if (colValue > 0) { left = i; break; } } if (left == 0) { return 1; } for (; i < src.cols; i++) { int colValue = getColSum(src, i); if (colValue == 0) { right = i; break; } } int width = right - left; Rect rect(left, 0, width, src.rows); leftImg = src(rect).clone(); Rect rectRight(right, 0, src.cols - right, src.rows); rightImg = src(rectRight).clone(); cutTop(leftImg, leftImg); return 0; } int getColSum(Mat src, int col) { int sum = 0; int height = src.rows; int width = src.cols; for (int i = 0; i < height; i++) { sum = sum + src.at <uchar>(i, col); } return sum; } void cutTop(Mat& src, Mat& dstImg)//上下切割 { int top, bottom; top = 0; bottom = src.rows; int i; for (i = 0; i < src.rows; i++) { int colValue = getRowSum(src, i); if (colValue > 0) { top = i; break; } } for (; i < src.rows; i++) { int colValue = getRowSum(src, i); if (colValue == 0) { bottom = i; break; } } int height = bottom - top; Rect rect(0, top, src.cols, height); dstImg = src(rect).clone(); } int getRowSum(Mat src, int row) { int sum = 0; int height = src.rows; int width = src.cols; for (int i = 0; i < width; i++) { sum += src.at <uchar>(row, i); } return sum; } void getPXSum(Mat &src, int &a)//获取所有像素点和 { threshold(src, src, 100, 255, CV_THRESH_BINARY); a = 0; for (int i = 0; i < src.rows; i++) { for (int j = 0; j < src.cols; j++) { a += src.at <uchar>(i, j); } } } int getSubtract(Mat &src, int TemplateNum) //两张图片相减 { Mat img_result; int min = 1000000; int serieNum = 0; for (int i = 0; i < TemplateNum; i++) { char name[20]; sprintf_s(name, ".\\AAA\\%dLeft.jpg", i); Mat Template = imread(name, CV_LOAD_IMAGE_GRAYSCALE); threshold(Template, Template, 100, 255, CV_THRESH_BINARY); threshold(src, src, 100, 255, CV_THRESH_BINARY); resize(src, src, Size(32, 48), 0, 0, CV_INTER_LINEAR); resize(Template, Template, Size(32, 48), 0, 0, CV_INTER_LINEAR);//调整尺寸 absdiff(Template, src, img_result); int diff = 0; getPXSum(img_result, diff); if (diff < min) { min = diff; serieNum = i; } } printf("%d ", serieNum); return serieNum; }