Niblack算法是比较出名的二值化算法，网上很多Niblack代码是基于Matlab的，本人觉得其速度比较慢，所以便基于OpenCV改写了其算法，具体参考的博客链接已经忘记了，希望博主原谅。如果缺少某些函数，比如最大值最小值函数，可以参考本人其他博客，里面会提供。废话不多说，直接上代码：
/** @brief 计算单通道灰度图像的平均值 @param src 单通道灰度图 */ static double GetMatAverage(const cv::Mat& src) { CV_Assert(src.type() == CV_8UC1); double sum = 0.0; for (int y = 0; y < src.rows; ++y) { for (int x = 0; x < src.cols; ++x) { int value = src.at<uchar>(y, x); sum += value; } } return sum / (src.rows * src.cols); } /** @brief 计算单通道灰度图像的标准差 @param src 单通道灰度图 */ static double GetMatStdDev(const cv::Mat& src, double meanValue) { CV_Assert(src.type() == CV_8UC1); double sum = 0.0; for (int y = 0; y < src.rows; ++y) { for (int x = 0; x < src.cols; ++x) { int value = src.at<uchar>(y, x); double var = (value - meanValue)*(value - meanValue); sum += var; } } double stdDev = std::sqrt(double(sum) / double(src.rows * src.cols)); return stdDev; } void Niblack(const cv::Mat & src, cv::Mat & dst, cv::Size wndSize) { CV_Assert(src.type() == CV_8UC1); CV_Assert((wndSize.width % 2 == 1) && (wndSize.height % 2 == 1)); CV_Assert((wndSize.width <= src.cols) && (wndSize.height <= src.rows)); cv::Mat flag = cv::Mat::zeros(src.rows, src.cols, CV_64FC1); for (int y = wndSize.height / 2; y <= src.rows - wndSize.height / 2 - 1; ++y) { for (int x = wndSize.width / 2; x <= src.cols - wndSize.width / 2 - 1; ++x) { int value = src.at<uchar>(y, x); cv::Point center = cv::Point(x, y); cv::Point topLeftPoint = cv::Point(x - wndSize.width / 2, y - wndSize.height / 2); cv::Rect wnd = cv::Rect(topLeftPoint.x, topLeftPoint.y, wndSize.width, wndSize.height); cv::Mat roiMat = src(wnd); double avgValue = GetMatAverage(roiMat); double dev = GetMatStdDev(roiMat, avgValue); // 这里是0.2 double flagValue = avgValue + 0.2 * dev; flag.at<double>(y, x) = flagValue; } } dst = cv::Mat::zeros(src.rows, src.cols, CV_8UC1); for (int y = 0; y < src.rows; ++y) { for (int x = 0; x < src.cols; ++x) { double flagValue = flag.at<double>(y, x); int value = src.at<uchar>(y, x); if (value > flagValue) { dst.at<uchar>(y, x) = 255; } else { dst.at<uchar>(y, x) = 0; } } } }文章来源: 基于opencv的Niblack二值化算法