OpenCV图像二值化

1.二值图像

• 灰度图像 0 - 255
• 二值图像 0（黑） / 255（白）

2.二值分割

五种阈值分割方法（阈值T）：

• 大于T为255，小于T为0

• 大于T为0，小于T为255

• 小于T为原值 else T

• 小于T为0 else 原值

• 大于T为0 else 原值

    QString appPath = QCoreApplication::applicationDirPath();QString imagePath = appPath + "/A.jpg";Mat img = cv::imread(imagePath.toStdString()); if (img.empty()) {return;}namedWindow("input", WINDOW_AUTOSIZE);imshow("input", img);//To gray imageMat gray,binary;cvtColor(img, gray, COLOR_BGR2GRAY);imshow("gray", gray);//二值化threshold(gray, binary, 127, 255, THRESH_BINARY);imshow("THRESH_BINARY", binary);threshold(gray, binary, 127, 255, THRESH_BINARY_INV);imshow("THRESH_BINARY_INV", binary);//阈值化threshold(gray, binary, 127, 255, THRESH_TRUNC);imshow("THRESH_TRUNC", binary);threshold(gray, binary, 127, 255, THRESH_TOZERO);imshow("THRESH_TOZERO", binary);threshold(gray, binary, 127, 255, THRESH_TOZERO_INV);imshow("THRESH_TOZERO_INV", binary);waitKey();destroyAllWindows();

3.阈值

（1）全局阈值

Scalar m = mean(gray);
threshold(gray, binary, m[0], 255, THRESH_BINARY);
imshow("THRESH_BINARY", binary);//OTSU
double m_otsu = threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_OTSU);
imshow("THRESH_BINARY_OTSU", binary);//三角法:X光片等
double m_triangle = threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_TRIANGLE);
imshow("THRESH_BINARY_TRIANGLE", binary);

（2）自适应阈值

//均值c
adaptiveThreshold(gray, binary, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 25,10);
imshow("ADAPTIVE_THRESH_MEAN_C", binary);//高斯c
adaptiveThreshold(gray, binary, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 25, 10);
imshow("ADAPTIVE_THRESH_GAUSSIAN_C", binary);