采用Zbar第三方库，实现二维码定位，并识别内容，解决了中文乱码

#include<iostream> #include "zbar.h" #include <opencv2/opencv.hpp> #include<codecvt> using namespace std; using namespace zbar; //添加zbar名称空间 using namespace cv; bool WideStringToString(const std::wstring& src, std::string &str) { std::locale sys_locale(""); const wchar_t* data_from = src.c_str(); const wchar_t* data_from_end = src.c_str() + src.size(); const wchar_t* data_from_next = 0; int wchar_size = 4; char* data_to = new char[(src.size() + 1) * wchar_size]; char* data_to_end = data_to + (src.size() + 1) * wchar_size; char* data_to_next = 0; memset(data_to, 0, (src.size() + 1) * wchar_size); typedef std::codecvt<wchar_t, char, mbstate_t> convert_facet; mbstate_t out_state = { 0 }; auto result = std::use_facet<convert_facet>(sys_locale).out( out_state, data_from, data_from_end, data_from_next, data_to, data_to_end, data_to_next); if (result == convert_facet::ok) { str = data_to; delete[] data_to; return true; } delete[] data_to; return false; } bool StringToWideString(const std::string& src, std::wstring &wstr) { std::locale sys_locale(""); const char* data_from = src.c_str(); const char* data_from_end = src.c_str() + src.size(); const char* data_from_next = 0; wchar_t* data_to = new wchar_t[src.size() + 1]; wchar_t* data_to_end = data_to + src.size() + 1; wchar_t* data_to_next = 0; wmemset(data_to, 0, src.size() + 1); typedef std::codecvt<wchar_t, char, mbstate_t> convert_facet; mbstate_t in_state = { 0 }; auto result = std::use_facet<convert_facet>(sys_locale).in( in_state, data_from, data_from_end, data_from_next, data_to, data_to_end, data_to_next); if (result == convert_facet::ok) { wstr = data_to; delete[] data_to; return true; } delete[] data_to; return false; } bool WCharStringToUTF8String(const std::wstring &wstr, std::string &u8str) { std::wstring_convert<std::codecvt_utf8<wchar_t>> conv; u8str = conv.to_bytes(wstr); return true; } bool UTF8StringToWCharString(const std::string &u8str, std::wstring &wstr) { std::wstring_convert<std::codecvt_utf8<wchar_t> > conv; wstr = conv.from_bytes(u8str); return true; } //当类型为条形码时候，用来确定位置 void calcu_grads(Mat& src) { Mat imageGray, imageGuussian; Mat imageSobelX, imageSobelY, imageSobelout; //原图像大小调整，提高效率 //resize(src,image,Size(500,500)); //imshow("二维码原图",image); cvtColor(src,imageGray,CV_BGR2GRAY); GaussianBlur(imageGray,imageGuussian,Size(3,3),0); Mat imageX16S, imageY16S; Sobel(imageGuussian,imageX16S,CV_16S,1,0,3,1,0,4); Sobel(imageGuussian, imageY16S, CV_16S, 0, 1, 3, 1, 0, 4); convertScaleAbs(imageX16S,imageSobelX,1,0); convertScaleAbs(imageY16S,imageSobelY,1,0); imageSobelout = imageSobelX - imageSobelY; blur(imageSobelout,imageSobelout,Size(3,3)); Mat imageThreshold; threshold(imageSobelout,imageThreshold,180,255,CV_THRESH_BINARY); Mat element = getStructuringElement(0,Size(7,7)); //开操作：先腐蚀后膨胀的操作称之为开操作。它具有消除细小物体，在纤细处分离物体和平滑较大物体边界的作用。 //闭操作：先膨胀后腐蚀的操作称之为闭操作。它具有填充物体内细小空洞，连接邻近物体和平滑边界的作用。 morphologyEx(imageThreshold,imageThreshold,MORPH_CLOSE,element); //imshow("threshold", imageThreshold); erode(imageThreshold,imageThreshold,element); //imshow("erode", imageThreshold); dilate(imageThreshold,imageThreshold,element); dilate(imageThreshold, imageThreshold, element); dilate(imageThreshold, imageThreshold, element); //imshow("2.膨胀图",imageThreshold); vector<vector<Point>> contours; vector<Vec4i> hiera; //CV_CHAIN_APPROX_NONE获取轮廓上所有像素点 //CV_RETR_EXTERNALCV_RETR_EXTERNAL只检测最外围轮廓，包含在外围轮廓内的内围轮廓被忽略， //CV_RETR_LIST 检测所有的轮廓，包括内围、外围轮廓，但是检测到的轮廓不建立等级关系，彼此之间独立，没有等级关系，这就意味着这个检索模式下不存在父轮廓或内嵌轮廓， findContours(imageThreshold,contours,hiera,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE); int max_area = 0; int max_index=0; for (int i = 0; i < contours.size(); i++) { Rect rect = boundingRect((Mat)contours[i]); if (rect.area() > max_area) { max_area = rect.area(); max_index = i; } } Rect temp = boundingRect((Mat)contours[max_index]); rectangle(src,temp,Scalar(0,0,255),3); } void ZbarDecoder(Mat& img) { ImageScanner scanner; scanner.set_config(ZBAR_NONE, ZBAR_CFG_ENABLE, 1); Mat imgout; cvtColor(img, imgout, CV_RGB2GRAY); int width = img.cols; int height = img.rows; uchar *raw = (uchar *)imgout.data; Image image(width, height, "Y800", raw, width * height); int n = scanner.scan(image); Image::SymbolIterator symbol = image.symbol_begin(); for (; symbol != image.symbol_end(); ++symbol) { vector<Point> vp; cout << "Decoded："<<symbol->get_type_name() << endl << endl; wstring str; string str1; UTF8StringToWCharString(symbol->get_data(),str); WideStringToString(str, str1); cout << str1; //cout << "Symbol："<< symbol->get_data() << endl << endl; if (symbol->get_type_name()=="QR-Code") { int n = symbol->get_location_size(); for (int i = 0; i<n; i++) { vp.push_back(Point(symbol->get_location_x(i), symbol->get_location_y(i))); } RotatedRect r = minAreaRect(vp); Point2f pts[4]; r.points(pts); for (int i = 0; i < 4; i++) { line(img, pts[i], pts[(i + 1) % 4], Scalar(0,0,255), 3); } } else { Mat res; calcu_grads(img); } } imshow("img", img); waitKey(); } int main() { Mat image = imread("w3.jpg"); if (!image.data) { cout << "The picture is empty!" << endl; system("pause"); return 0; } Mat res; ZbarDecoder(image); system("pause"); return 0; }