OpenCV-Otsu阈值分割
步骤：1、计算累加直⽅图；2、计算⼀阶累积矩；3、计算图像的总体灰度平均值；4、计算每个灰度值对应的⽅差；5、找到⽬标阈值。C++：
#include<opencv2/opencv.hpp>
#include<iostream>
using namespace std;
using namespace cv;
//计算图像灰度直⽅图
Mat calcgrayhist(const Mat&image)
{
Mat histogram = Mat::zeros(Size(256,1), CV_32SC1);
//图像宽⾼
int rows = ws;
int cols = ls;
超虐小说
for(int i =0; i < rows; i++)
{
for(int j =0; j < rows; j++)
{
int index =int(image.at<uchar>(i, j));
histogram.at<int>(0, index)+=1;
}
}
return histogram;
};
//OTSU
int OTSU(const Mat&image,Mat &OTSU_image)
{
int rows = ws;
int cols = ls;
把单元格一分为二Mat histogram =calcgrayhist(image);
//归⼀化直⽅图
Mat normhist;
//计算累加直⽅图和⼀阶累积矩
Mat zeroaccumulate = Mat::zeros(Size(256,1), CV_32FC1);
Mat oneaccumulate = Mat::zeros(Size(256,1), CV_32FC1);
for(int i =0; i <256; i++)
{
if(i ==0)
{
zeroaccumulate.at<float>(0, i)= normhist.at<float>(0, i);
oneaccumulate.at<float>(0, i)=i * normhist.at<float>(0, i);
}
el
{
zeroaccumulate.at<float>(0, i)= zeroaccumulate.at<float>(0, i-1)
+normhist.at<float>(0, i);
oneaccumulate.at<float>(0, i)= oneaccumulate.at<float>(0, i -1)
+i* normhist.at<float>(0, i);
}
}
//计算间类⽅差
Mat variance= Mat::zeros(Size(256,1), CV_32FC1);
float mean = oneaccumulate.at<float>(0,255);
for(int i =0; i <255; i++)
{
if(zeroaccumulate.at<float>(0, i)==0|| zeroaccumulate.at<float>(0, i)==1)
variance.at<float>(0, i)=0;
el
{
float cofficient = zeroaccumulate.at<float>(0, i)*(1.0-
float cofficient = zeroaccumulate.at<float>(0, i)*(1.0-
zeroaccumulate.at<float>(0, i));
variance.at<float>(0, i)=pow(mean*zeroaccumulate.at<float>(0, i)
- oneaccumulate.at<float>(0, i),2.0)/ cofficient;
}
}
/
/找到阈值；
Point maxloc;
//计算矩阵中最⼤值
minMaxLoc(variance,NULL,NULL,NULL,&maxloc);
int otsuthreshold = maxloc.x;
threshold(image, OTSU_image, otsuthreshold,255, THRESH_BINARY); return otsuthreshold;
};
int main()
{
Mat img, gray_img,dst;
img =imread("D:/testimage/orange.jpg");
cvtColor(img, gray_img, COLOR_BGR2GRAY);
OTSU(gray_img,dst);
imshow("otsu image", dst);
waitKey(0);
笑话大全爆笑图片return0;
};
结果：
Python：
import cv2 as cv
import numpy as np
import math
def calc_grayhist(image):
#图像宽⾼
rows,cols=image.shape
s([256],np.uint64)
for i in range(rows):
for j in range(cols):
grayhist[image[i][j]]+=1excal
return grayhist
def OTSU(image):
rows, cols = image.shape
简历特长爱好grayhist=calc_grayhist(image)
#归⼀化直⽅图
uniformgrayhist=grayhist/float(rows*cols)
#计算零阶累积矩和⼀阶累积矩
zeroaccumulat = np.zeros([256],np.float32)
oneaccumulat = np.zeros([256], np.float32)
for k in range(256):
if k==0:subtotal
zeroaccumulat[k]=uniformgrayhist[0]
oneaccumulat[k]=k*uniformgrayhist[0]
el:
zeroaccumulat[k]=zeroaccumulat[k-1]+uniformgrayhist[k]
oneaccumulat[k]=oneaccumulat[k-1]+k*uniformgrayhist[k]
#计算间类⽅差
s([256],np.float32)
for k in range(256):
if zeroaccumulat[k]==0or zeroaccumulat[k]==1:
variance[k]=0
el:
variance[k]=math.pow(oneaccumulat[255]*zeroaccumulat[k]-
oneaccumulat[k],2)/(zeroaccumulat[k]*(1.0-zeroaccumulat[k])) threshLoc=np.where(variance[0:255]==np.max(variance[0:255]))
thresh=threshLoc[0][0]
#阈值分割
py(image)
threshold[threshold>thresh]=255
threshold[threshold <= thresh]=0
return threshold
if __name__=="__main__":
img=cv.imread("D:/testimage/cxk.jpg")
gray_dst = cv.cvtColor(img, cv.COLOR_BGR2GRAY)钻石鉴别
Otsu_dst=OTSU(gray_dst)
cv.imshow("gray dst",gray_dst)
cv.imshow("Otsu dst", Otsu_dst)
血压怎么降
cv.imwrite("D:/testimage/result-cxk.jpg",Otsu_dst)
cv.waitKey(0)
cv.destroyAllWindows()
