opencv-043-图像二值寻找算法(TRIANGLE)

发表于 | 分类于

知识点

OpenCV中支持的有OTSU与Triangle两种直方图阈值寻找算法。OTSU基于类内最小方差实现阈值寻找, 它对有两个波峰之间有一个波谷的直方图特别好,但是有时候图像的直方图只有一个波峰,这个时候使用TRIANGLE方法寻找阈值是比较好的一个选择。

注意：两个波峰 –> OTSU ， 一个波峰 –> TRANGLE

OpenCV中TRIANGLE算法使用只需要在threshold函数的type类型声明THRESH_TRIANGLE即可

代码（c++,python）

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

/*
 * 图像二值寻找算法 – TRIANGLE
 */
int main() {
    Mat src = imread("../images/test.png");
    if (src.empty()) {
        cout << "could not load image.." << endl;
    }
    imshow("input", src);

    // 自动阈值寻找与二值化
    Mat gray, binary;
    cvtColor(src, gray, COLOR_BGR2GRAY);
    double T = threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_TRIANGLE);
    cout << "threshold : " << T << endl;
    imshow("binary", binary);

    waitKey(0);
    return 0;
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
import cv2 as cv
import numpy as np
import tensorflow as tf

tf.enable_eager_execution()
#
# THRESH_BINARY = 0
# THRESH_BINARY_INV = 1
# THRESH_TRUNC = 2
# THRESH_TOZERO = 3
# THRESH_TOZERO_INV = 4
#
src = cv.imread("D:/images/lena.jpg")
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", src)
h, w = src.shape[:2]


# 自动阈值分割 TRIANGLE
gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_TRIANGLE)
print("ret :", ret)
cv.imshow("binary", binary)

result = np.zeros([h, w*2, 3], dtype=src.dtype)
result[0:h,0:w,:] = src
result[0:h,w:2*w,:] = cv.cvtColor(binary, cv.COLOR_GRAY2BGR)
cv.putText(result, "input", (10, 30), cv.FONT_ITALIC, 1.0, (0, 0, 255), 2)
cv.putText(result, "binary, threshold = " + str(ret), (w+10, 30), cv.FONT_ITALIC, 1.0, (0, 0, 255), 2)
cv.imshow("result", result)
cv.imwrite("D:/binary_result.png", result)

cv.waitKey(0)
cv.destroyAllWindows()

结果

代码地址

github