【图像处理】条形码与二维码的定位与识别

代码实现简单环境下的条形码与二维码的定位与识别：

原图：

#include<iostream>
#include<opencv2\opencv.hpp>
#include<zbar.h>using namespace std;
using namespace cv;
using namespace zbar;//寻找最大的轮廓
static vector<cv::Point> FindBiggestContour(Mat src)
{int imax = 0; //代表最大轮廓的序号int imaxcontour = -1; //代表最大轮廓的大小std::vector<std::vector<cv::Point>>contours;findContours(src, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);for (int i = 0; i<contours.size(); i++){int itmp = contourArea(contours[i]);//这里采用的是轮廓大小if (imaxcontour < itmp){imax = i;imaxcontour = itmp;}}return contours[imax];
}//获取二维码
void detect_decode_qrcode()
{Mat img = imread("barcode_qrcode.jpg");if (img.empty()){cout << "reading images fails" << endl;}//灰度化Mat img_gray, img_bin;cvtColor(img, img_gray, COLOR_BGR2GRAY);threshold(img_gray, img_bin, 100, 255, THRESH_OTSU | THRESH_BINARY_INV);  //THRESH_BINARY_INV  二值化取反						 vector<vector<Point>> contours, contours2; //找轮廓  找到的轮廓按照树的方式排列vector<Vec4i> hierarchy;findContours(img_bin, contours, hierarchy, RETR_TREE, CHAIN_APPROX_NONE);int c = 0, ic = 0, area = 0;int parentIdx = -1;for (int i = 0; i < contours.size(); i++){											//遍历所有的大轮廓									if (hierarchy[i][2] != -1 && ic == 0)  //如果 这个大轮廓没有父轮廓 hierarchy[i][2] != -1 说明他是存在子轮廓的{parentIdx = i;ic++;}else if (hierarchy[i][2] != -1){ic++;}//最外面的清0else if (hierarchy[i][2] == -1){ic = 0;parentIdx = -1;}//找到定位点信息if (ic == 2){contours2.push_back(contours[parentIdx]);ic = 0;parentIdx = -1;}}//二维码中间是应该有三个特征轮廓的，如果等于3 那么就认为它是有二维码的if (contours2.size() != 3){printf("finding 3 rects fails \n");}//把二维码最外面的轮廓构造成一个新的点集Rect new_rect;vector<Point> all_points;for (int i = 0; i < contours2.size(); i++){for (int j = 0; j < contours2[i].size(); j++)all_points.push_back(contours2[i][j]);}new_rect = boundingRect(all_points);  //根据二维码构成得点集，找到一个最小的外包所有点集 的矩形//  Rect rect(230, 5, 280, 290);//左上坐标（x,y）和矩形的长(x)宽(y)//  cv::rectangle(src, rect, Scalar(255, 0, 0),1, LINE_8,0);rectangle(img, new_rect, Scalar(0, 0, 255), 8, 0);Mat result_img = img_gray(new_rect);   //将找到的矩形 放进灰度图中，这样图片就可以根据矩形切割出来了ImageScanner scanner;scanner.set_config(ZBAR_QRCODE, ZBAR_CFG_ENABLE, 1);int width = result_img.step;  //因为这一小部分是截取出来的int height = result_img.rows;uchar *raw = (uchar *)result_img.data;Image imageZbar(width, height, "Y800", raw, width * height);scanner.scan(imageZbar);Image::SymbolIterator symbol = imageZbar.symbol_begin();if (imageZbar.symbol_begin() == imageZbar.symbol_end()){cout << "查询二维码失败，请检查图片！" << endl;}for (; symbol != imageZbar.symbol_end(); ++symbol){cout << "类型：" << endl << symbol->get_type_name() << endl << endl;cout << "二维码：" << endl << symbol->get_data() << endl << endl;}imageZbar.set_data(NULL, 0);//imshow("mat",img);imshow("mat1", result_img);
}//获取条形码
void detect_decode_barcode()
{Mat src = imread("barcode_qrcode.jpg");if (src.empty()){cout << "reading images fails" << endl;}Mat sobel;Mat canny;Mat canny_output;//1、//灰度化Mat gray;cvtColor(src, gray, COLOR_BGR2GRAY); //2、二值化//Canny(gray, canny, 100, 255);Mat bin;threshold(gray, bin, 0, 255, THRESH_OTSU | THRESH_BINARY_INV);//3、形态学滤波Mat element = getStructuringElement(MORPH_ELLIPSE, Size(12, 2));morphologyEx(bin, bin, MORPH_DILATE, element); //形态学滤波  找到条形码 大白//morphologyEx(canny, canny, MORPH_ERODE, element);//4、寻找最大的轮廓Rect boundRect = boundingRect(Mat(FindBiggestContour(bin)));Mat result_img = gray(boundRect);imshow("mat2", result_img);ImageScanner scanner;scanner.set_config(ZBAR_NONE, ZBAR_CFG_ENABLE, 1);int width = result_img.step;int height = result_img.rows;uchar *raw = (uchar *)result_img.data;Image imageZbar(width, height, "Y800", raw, width * height);scanner.scan(imageZbar); //扫描条码      Image::SymbolIterator symbol = imageZbar.symbol_begin();if (imageZbar.symbol_begin() == imageZbar.symbol_end()){cout << "查询条码失败，请检查图片！" << endl;}for (; symbol != imageZbar.symbol_end(); ++symbol){cout << "类型：" << endl << symbol->get_type_name() << endl << endl;cout << "条码：" << endl << symbol->get_data() << endl << endl;}imageZbar.set_data(NULL, 0);
}
//主函数
int main()
{detect_decode_qrcode(); detect_decode_barcode();waitKey(0);return 0;
}

检测结果图：