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基于ZBar做二维码识别，识别率很低，为了提高识别率，可以先将图像进行灰度化处理再进行识别，准确率将会有很大提升。

#include <vector>
#include <algorithm>
#include <string>
#include <math.h>
#include <iostream>
#include<map>#include <cv.h>
#include <highgui.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>#ifdef _DEBUG
#pragma comment(lib, "opencv_world300d.lib")
#else
#pragma comment(lib, "opencv_world300.lib")
#endif#include <zbar.h>
using namespace zbar;
#pragma comment(lib, "libzbar-0.lib")using namespace cv;
using namespace std;namespace QRCode{std::string GetQRInBinImg(Mat binImg);std::string ZbarDecoder(Mat img);//对二值图像进行识别，如果失败则开运算进行二次识别std::string GetQR(Mat img){Mat binImg;Mat adaptiveImg;double thre = threshold(img, binImg, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY_INV);//threshold 第一个参数即原图像必须为灰度图std::string result;result = GetQRInBinImg(binImg);if(result.empty())//如果阈值otsuthreshold失败，则采用高斯自适应阈值化，可以识别出一定的控制阈值也识别不出来的二维码{cv::adaptiveThreshold(img, adaptiveImg, 255, ADAPTIVE_THRESH_GAUSSIAN_C, cv::THRESH_BINARY, 33, 0);//threshold第一个参数即原图像必须为灰度图,最佳33result = GetQRInBinImg(adaptiveImg);}thre = thre/2;//ostu和自适应阈值都失败，将从ostu阈值的一般开始控制阈值不断增长while (result.empty() && thre<255){threshold(img, binImg, thre, 255, cv::THRESH_BINARY);result = GetQRInBinImg(binImg);thre += 5;//阈值步长设为5，步长越大，识别率越低，速度越快,对于当前测试图片的情况为5识别出来的最多}return result;}//主体函数std::string GetQRInBinImg(Mat binImg){    std::string result = ZbarDecoder(binImg);if (result.empty()){Mat openImg;Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));morphologyEx(binImg, openImg, MORPH_OPEN, element);result = ZbarDecoder(openImg);}return result;}//zbar接口std::string ZbarDecoder(Mat img){float point[8];string result;std::string res;ImageScanner scanner;const void *raw = (&img)->data;scanner.set_config(ZBAR_NONE, ZBAR_CFG_ENABLE, 1);Image image(img.cols, img.rows, "Y800", raw, img.cols * img.rows);int n = scanner.scan(image);Image::SymbolIterator symbol = image.symbol_begin();res = image.symbol_begin()->get_data();cout << res.c_str() << endl;image.set_data(NULL, 0);return res;}
}

 调用示例：

cv::Mat src = cv::imread(lpszFileName);
Mat imageGray;
cvtColor(src, imageGray, CV_RGB2GRAY);
string ret = QRCode::GetQR(imageGray);
if ( !ret.empty() )
{TRACE("图片%s...识别结果=[%s]\n", lpszFileName, ret.c_str());
}
else
{TRACE("图片%s...[%s]\n", lpszFileName, "未识别");
}