问题描述
我试图用otsu执行多阈值。我目前使用的方法实际上是通过最大化类间方差，我已经设法获得相同的阈值给定的OpenCV库。但是，这只是通过运行otsu方法一次。
关于如何做多级阈值或相当递归阈值的文档是有限的。我在获得原始otsu的价值后，我该怎么办？感谢一些提示，我一直在玩代码，添加一个外部循环，但下一个值计算总是254任何给定的图像：（
我的代码如果需要：
//首先计算直方图
cv :: Mat imageh; //图像编辑为灰度直方图目的
// imageh = image; //以下删除和取消注释;
cv :: cvtColor（image，imageh，CV_BGR2GRAY）;
int histSize [1] {256}; // number of bins
float hranges [2] = {0.0，256.0}; // min andax像素值
const float * ranges [1] = {hranges};
int channels [1] = {0}; //只使用一个通道
cv :: MatND hist;
//计算直方图
calcHist（& imageh，1 ，channels，cv :: Mat（），hist，1，histSize，ranges）;
IplImage * im = new IplImage（imageh）; //将图像分配给IplImage指针
IplImage * finalIm = cvCreateImage（cvSize（im-> width，im-> height），IPL_DEPTH_8U，1）;
double otsuThreshold = cvThreshold（im，finalIm，0，255，cv :: THRESH_BINARY | cv :: THRESH_OTSU）;
cout<<opencv otsu gives<< otsuThreshold<< endl;
int totalNumberOfPixels = imageh.total（）;
cout<<总像素数为<<< totalNumberOfPixels< endl;
float sum = 0;
for（int t = 0; t {
sum + = t * hist.at< float>（t）
}
cout<<sum is<< sum<< endl;
float sumB = 0; // background of background
int wB = 0; //背景权重
int wF = 0; //前景的权重
float varMax = 0;
int threshold = 0;
//运行迭代以找到类间方差之间的最大值（类方差之间的最大化）
for（int t = 0; t {
wB + = hist.at< float>（t）; // Weight Background
if（wB == 0）continue;
wF = totalNumberOfPixels - wB; // Weight Foreground
if（wF == 0）break;
sumB + =（float）（t * hist.at< float>（t））;
float mB = sumB / wB; //平均背景
float mF =（sum - sumB）/ wF; //平均前景
//计算类之间的变异
float varBetween =（float）wB *（float）wF *（mB - mF）*（mB - mF）
//检查是否找到了新的最大值
if（varBetween> varMax）{
varMax = varBetween;
threshold = t;
}
}
cout<<阈值为
要将Otsu的阈值法扩展到多级阈值类间方差方程变为：
希望这有助。
I am trying to carry out multi-thresholding with otsu. The method I am using currently is actually via maximising the between class variance, I have managed to get the same threshold value given as that by the OpenCV library. However, that is just via running otsu method once.
Documentation on how to do multi-level thresholding or rather recursive thresholding is rather limited. Where do I do after obtaining the original otsu's value? Would appreciate some hints, I been playing around with the code, adding one external for loop, but the next value calculated is always 254 for any given image:(
My code if need be:
//compute histogram first
cv::Mat imageh; //image edited to grayscale for histogram purpose
//imageh=image; //to delete and uncomment below;
cv::cvtColor(image, imageh, CV_BGR2GRAY);
int histSize[1] = {256}; // number of bins
float hranges[2] = {0.0, 256.0}; // min andax pixel value
const float* ranges[1] = {hranges};
int channels[1] = {0}; // only 1 channel used
cv::MatND hist;
// Compute histogram
calcHist(&imageh, 1, channels, cv::Mat(), hist, 1, histSize, ranges);
IplImage* im = new IplImage(imageh);//assign the image to an IplImage pointer
IplImage* finalIm = cvCreateImage(cvSize(im->width, im->height), IPL_DEPTH_8U, 1);
double otsuThreshold= cvThreshold(im, finalIm, 0, 255, cv::THRESH_BINARY | cv::THRESH_OTSU );
cout<<"opencv otsu gives "<<otsuThreshold<<endl;
int totalNumberOfPixels= imageh.total();
cout<<"total number of Pixels is " <<totalNumberOfPixels<< endl;
float sum = 0;
for (int t=0 ; t<256 ; t++)
{
sum += t * hist.at<float>(t);
}
cout<<"sum is "<<sum<<endl;
float sumB = 0; //sum of background
int wB = 0; // weight of background
int wF = 0; //weight of foreground
float varMax = 0;
int threshold = 0;
//run an iteration to find the maximum value of the between class variance(as between class variance shld be maximise)
for (int t=0 ; t<256 ; t++)
{
wB += hist.at<float>(t); // Weight Background
if (wB == 0) continue;
wF = totalNumberOfPixels - wB; // Weight Foreground
if (wF == 0) break;
sumB += (float) (t * hist.at<float>(t));
float mB = sumB / wB; // Mean Background
float mF = (sum - sumB) / wF; // Mean Foreground
// Calculate Between Class Variance
float varBetween = (float)wB * (float)wF * (mB - mF) * (mB - mF);
// Check if new maximum found
if (varBetween > varMax) {
varMax = varBetween;
threshold = t;
}
}
cout<<"threshold value is: "<<threshold;
To extend Otsu's thresholding method to multi-level thresholding the between class variance equation becomes:
Here is my C# implementation of Otsu Multi for 2 thresholds:
/* Otsu (1979) - multi */
Tuple < int, int > otsuMulti(object sender, EventArgs e) {
//image histogram
int[] histogram = new int[256];
//total number of pixels
int N = 0;
//accumulate image histogram and total number of pixels
foreach(int intensity in image.Data) {
if (intensity != 0) {
histogram[intensity] += 1;
N++;
}
}
double W0K, W1K, W2K, M0, M1, M2, currVarB, optimalThresh1, optimalThresh2, maxBetweenVar, M0K, M1K, M2K, MT;
optimalThresh1 = 0;
optimalThresh2 = 0;
W0K = 0;
W1K = 0;
M0K = 0;
M1K = 0;
MT = 0;
maxBetweenVar = 0;
for (int k = 0; k <= 255; k++) {
MT += k * (histogram[k] / (double) N);
}
for (int t1 = 0; t1 <= 255; t1++) {
W0K += histogram[t1] / (double) N; //Pi
M0K += t1 * (histogram[t1] / (double) N); //i * Pi
M0 = M0K / W0K; //(i * Pi)/Pi
W1K = 0;
M1K = 0;
for (int t2 = t1 + 1; t2 <= 255; t2++) {
W1K += histogram[t2] / (double) N; //Pi
M1K += t2 * (histogram[t2] / (double) N); //i * Pi
M1 = M1K / W1K; //(i * Pi)/Pi
W2K = 1 - (W0K + W1K);
M2K = MT - (M0K + M1K);
if (W2K <= 0) break;
M2 = M2K / W2K;
currVarB = W0K * (M0 - MT) * (M0 - MT) + W1K * (M1 - MT) * (M1 - MT) + W2K * (M2 - MT) * (M2 - MT);
if (maxBetweenVar < currVarB) {
maxBetweenVar = currVarB;
optimalThresh1 = t1;
optimalThresh2 = t2;
}
}
}
return new Tuple(optimalThresh1, optimalThresh2);
}
And this is the result I got by thresholding an image scan of soil with the above code:
(T1 = 110, T2 = 147).
Hope this helps.
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