基本阈值操作

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图像阈值

阈值 是什么？简单点说是把图像分割的标尺，这个标尺是根据什么产生的，阈值产生算法？阈值类型。（Binary segmentation）

阈值类型




阈值类型一阈值二值化(threshold binary)



阈值类型一阈值反二值化(threshold binary Inverted)




阈值类型一截断 (truncate)


阈值类型一阈值取零 (threshold to zero)





阈值类型一阈值反取零 (threshold to zero inverted)

[C++] 纯文本查看 复制代码

/*
注意:
        THRESH_BINARY     = 0, //!< \f[\texttt{dst} (x,y) =  \fork{\texttt{maxval}}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{0}{otherwise}\f]
        THRESH_BINARY_INV = 1, //!< \f[\texttt{dst} (x,y) =  \fork{0}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{maxval}}{otherwise}\f]
        THRESH_TRUNC      = 2, //!< \f[\texttt{dst} (x,y) =  \fork{\texttt{threshold}}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{src}(x,y)}{otherwise}\f]
        THRESH_TOZERO     = 3, //!< \f[\texttt{dst} (x,y) =  \fork{\texttt{src}(x,y)}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{0}{otherwise}\f]
        THRESH_TOZERO_INV = 4, //!< \f[\texttt{dst} (x,y) =  \fork{0}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{src}(x,y)}{otherwise}\f]
        THRESH_MASK       = 7,
        THRESH_OTSU       = 8, //!< flag, use Otsu algorithm to choose the optimal threshold value
        THRESH_TRIANGLE   = 16 //!< flag, use Triangle algorithm to choose the optimal threshold value
*/
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;

Mat src, gray_src, dst;
//阈值二值化的模式0-4 参考注意点,默认设为0
int threshold_mod=0;
//阈值二值化最大值,一共5种模式0-4
int threshold_mod_max=4;
//--------------------------------------

//设定阈值
int threshold_value = 127;
//设定最大阈值
int threshold_max = 255;
// 定义输出窗口标题
char output_title[] = "输出窗口";

// -----------------------------
//声明函数
void Thershold_Demo(int, void*);

int main(int argc, char** argv) {
        src = imread("D:/IDE/opencv-3.1.0/demo.jpg");
        if (!src.data) {
                printf("加载图片异常\n");
                return -1;
        }
        namedWindow("input", CV_WINDOW_AUTOSIZE);
        namedWindow(output_title, CV_WINDOW_AUTOSIZE);
        imshow("input", src);


        createTrackbar("拖动条:",output_title, &threshold_value, threshold_max, Thershold_Demo);
        //创建效果拖动条
        createTrackbar("模式:", output_title, &threshold_mod, threshold_mod_max, Thershold_Demo);
        //阈值二值化的模式的变化
        Thershold_Demo(threshold_value, 0);
        waitKey(0);
        return 0;
}
void Thershold_Demo(int val, void*  ) {

        
                switch (threshold_mod)
                {
                case 0: cout << "THRESH_BINARY模式(阈值二值化)" << endl; break;
                case 1: cout << "THRESH_BINARY_INV模式(阈值反二值化)" << endl; break;
                case 2: cout << "THRESH_TRUNC模式(阈值截断)" << endl; break;
                case 3: cout << "THRESH_TOZERO模式(阈值取零)" << endl; break;
                case 4: cout << "THRESH_TOZERO_INV模式(阈值反取零)" << endl; break;
                default:
                        break;
                }
        



        printf("调整的数值为:%d\n", val);
        //转灰度图
        cvtColor(src, gray_src, CV_BGR2GRAY);
        //阈值的处理
        threshold(gray_src, dst, threshold_value, threshold_max, threshold_mod);
        imshow(output_title, dst);

}

自动寻找阈值:
THRESH_OTSU
THRESH_TRIANGLE

[C++] 纯文本查看 复制代码

/*
注意:
THRESH_OTSU THRESH_TRIANGLE处理的图像必须是8位单通道(灰度图)

自动寻找阈值
THRESH_OTSU
THRESH_TRIANGLE
*/
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
//声明函数
void demo(int, void*);
//定义滑块条最小值
int val = 0;

Mat src, gray_src,dst;

int main(int argc, char** argv) {
	
	src = imread("D:/IDE/opencv-3.1.0/demo.jpg");
	if (!src.data) {
		printf("加载图片异常\n");
		return -1;
	}
	namedWindow("input", CV_WINDOW_AUTOSIZE);

	namedWindow("CV_demo", CV_WINDOW_AUTOSIZE);
	//创建滑块条
	createTrackbar("模式调整:", "CV_demo",&val,4, demo);
	demo(0, 0);
	imshow("input", src);
	waitKey(0);
	return 0;
}
void demo(int, void*){
	//转灰度图
	cvtColor(src, gray_src, CV_BGR2GRAY);
	//通过THRESH_OTSU 自动获取阈值,处理效果
	//threshold(gray_src, dst, 0, 255, THRESH_OTSU|val);

	//通过THRESH_TRIANGLE 自动获取阈值,处理效果
	threshold(gray_src, dst, 0, 255, THRESH_TRIANGLE | val);
	imshow("CV_demo", dst);
}