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[threshold]基本阈值操作¶

参考：

Basic Thresholding Operations

opencv cvThreshold() cvAdaptiveThreshold()

使用OpenCV函数cv::threshold实现基本阈值操作

什么是阈值操作¶

阈值操作是最简单的分割方法，通过像素值的判断分离出目标和背景

函数cv::threshold提供了多种阈值操作，参考ThresholdTypes

THRESH_BINARY
THRESH_BINARY_INV
THRESH_TRUNC
THRESH_TOZERO
THRESH_TOZERO_INV
THRESH_OTSU
THRESH_TRIANGLE

假定将原图变形为一行，其像素值和阈值关系如下图所示

每列红色表示像素值大小，蓝色直线表示阈值

THRESH_BINARY¶

阈值操作如下：

如果像素值比阈值大，则设为最大值，否则，设为0。结果如下图所示

THRESH_BINARY_INV¶

阈值操作如下：

其操作与THRESH_BINARY相反。如果像素值比阈值大，则设为0，否则，设为最大值。结果如下图所示

THRESH_TRUNC¶

阈值操作如下：

如果像素值比阈值大，则设为最大值，否则，仍就是像素值。结果如下图所示

THRESH_TOZERO¶

阈值操作如下：

如果像素值比阈值大，仍就是像素值，否则，设为0。结果如下图所示

THRESH_TOZERO_INV¶

阈值操作如下：

其操作与THRESH_TOZERO相反。如果像素值比阈值大，则设为0，否则，仍就是像素值。结果如下图所示

THRESH_OTSU¶

使用OTSU算法计算最佳阈值。其实现参考：opencv 最大类间方差（大津法OTSU）

THRESH_TRIANGLE¶

使用Triangle算法计算最佳阈值

函数解析¶

CV_EXPORTS_W double threshold( InputArray src, OutputArray dst,
                               double thresh, double maxval, int type );

src：原图。可以是多通道，8位深度或者32位深度
dst：结果图像。大小和类型与原图一致
thresh：阈值
maxval：最大阈值。当阈值类型为THRESH_BINARY或THRESH_BINARY_INV时使用
type：阈值类型

头文件声明：#include <opencv2/imgproc.hpp>

源文件地址：/path/to/modules/imgproc/src/thresh.cpp

示例¶

#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>

using namespace cv;
using std::cout;

int threshold_value = 0;
int threshold_type = 3;
int const max_value = 255;
int const max_type = 6;
int const max_binary_value = 255;
Mat src, src_gray, dst;
const char *window_name = "Threshold Demo";
const char *trackbar_type =
        "Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted \n 5: Ostu \n "
        "6: Triangle";
const char *trackbar_value = "Value";

static void Threshold_Demo(int, void *) {
    /* 0: Binary
     1: Binary Inverted
     2: Threshold Truncated
     3: Threshold to Zero
     4: Threshold to Zero Inverted
    */
    if (threshold_type == 5) {
        threshold_type = THRESH_OTSU;
    } else if (threshold_type == 6) {
        threshold_type = THRESH_TRIANGLE;
    }
    threshold(src_gray, dst, threshold_value, max_binary_value, threshold_type);
    imshow(window_name, dst);
}

int main(int argc, char **argv) {
    String imageName("../stuff.jpg"); // by default
    if (argc > 1) {
        imageName = argv[1];
    }
    src = imread(samples::findFile(imageName), IMREAD_COLOR); // Load an image
    if (src.empty()) {
        cout << "Cannot read the image: " << imageName << std::endl;
        return -1;
    }
    cvtColor(src, src_gray, COLOR_BGR2GRAY); // Convert the image to Gray

    namedWindow(window_name, WINDOW_AUTOSIZE); // Create a window to display results
    createTrackbar(trackbar_type,
                   window_name, &threshold_type,
                   max_type, Threshold_Demo); // Create a Trackbar to choose type of Threshold
    createTrackbar(trackbar_value,
                   window_name, &threshold_value,
                   max_value, Threshold_Demo); // Create a Trackbar to choose Threshold value
    Threshold_Demo(0, 0); // Call the function to initialize

    waitKey();
    return 0;
}

创建两个滑动条，一个改变阈值类型，一个改变最小阈值