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图像的二值化就是将图像上的像素点的灰度值设置为0或255，这样将使整个图像呈现出明显的黑白效果。在数字图像处理中，二值图像占有非常重要的地位，图像的二值化使图像中数据量大为减少，从而能凸显出目标的轮廓。OpenCV中提供了函数cv::threshold();
注意:作者采用OpenCV 3.0.0
函数原型
参数说明
src：源图像，可以为8位的灰度图，也可以为32位的彩色图像。（两者由区别）
dst：输出图像
thresh：阈值
maxval：dst图像中最大值
type：阈值类型，可以具体类型如下：
| 编号 | 阈值类型枚举 |
注意
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| 1 | THRESH_BINARY |
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| 2 | THRESH_BINARY_INV |
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| 3 | THRESH_TRUNC |
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| 4 | THRESH_TOZERO |
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| 5 | THRESH_TOZERO_INV |
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| 6 | THRESH_MASK |
不支持
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| 7 | THRESH_OTSU |
不支持32位
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| 8 | THRESH_TRIANGLE |
不支持32位
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具体如下表
生成关系如下表
测试代码
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Mat gray;
cvtColor(src, gray, CV_BGR2GRAY);
// 全局二值化
int th = 100;
cv::Mat threshold1,threshold2,threshold3,threshold4,threshold5,threshold6,threshold7,threshold8;
cv::threshold(gray, threshold1, th, 255, THRESH_BINARY);
cv::threshold(gray, threshold2, th, 255, THRESH_BINARY_INV);
cv::threshold(gray, threshold3, th, 255, THRESH_TRUNC);
cv::threshold(gray, threshold4, th, 255, THRESH_TOZERO);
cv::threshold(gray, threshold5, th, 255, THRESH_TOZERO_INV);
//cv::threshold(gray, threshold6, th, 255, THRESH_MASK);
cv::threshold(gray, threshold7, th, 255, THRESH_OTSU);
cv::threshold(gray, threshold8, th, 255, THRESH_TRIANGLE);
cv::imshow("THRESH_BINARY", threshold1);
cv::imshow("THRESH_BINARY_INV", threshold2);
cv::imshow("THRESH_TRUNC", threshold3);
cv::imshow("THRESH_TOZERO", threshold4);
cv::imshow("THRESH_TOZERO_INV", threshold5);
//cv::imshow("THRESH_MASK", threshold6);
cv::imshow("THRESH_OTSU", threshold7);
cv::imshow("THRESH_TRIANGLE", threshold8);
cv::waitKey(0);
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测试结果
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原图
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THRESH_BINARY
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THRESH_BINARY_INV
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THRESH_TRUNC
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THRESH_TOZERO
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THRESH_TOZERO_INV
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THRESH_OTSU
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THRESH_TRIANGLE
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注意：
如果采用彩色图像进行计算会得到彩色效果，而不是预期的二值化结果
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彩色源图
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灰度源图
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