问题
I'm trying to use OpenCV's cv::threshold function (more specific THRESH_OTSU), only that I'd like to do it with a mask (any shape), so that the outside (background) is ignored during calculation.
Image is single channel (as it must be), red color bellow is only to mark an example polygon on an image.
I tried using adaptiveThreshold, but there are a couple of problems that make it inappropriate in my case.
回答1:
In general, you can simply compute the threshold using cv::threshold, and then copy the src image on dst using the inverted mask.
// Apply cv::threshold on all image
thresh = cv::threshold(src, dst, thresh, maxval, type);
// Copy original image on inverted mask
src.copyTo(dst, ~mask);
With THRESH_OTSU, however, you also need to compute the threshold value only on the masked image. The following code is a modified version of static double getThreshVal_Otsu_8u(const Mat& _src) in thresh.cpp:
double otsu_8u_with_mask(const Mat1b src, const Mat1b& mask)
{
const int N = 256;
int M = 0;
int i, j, h[N] = { 0 };
for (i = 0; i < src.rows; i++)
{
const uchar* psrc = src.ptr(i);
const uchar* pmask = mask.ptr(i);
for (j = 0; j < src.cols; j++)
{
if (pmask[j])
{
h[psrc[j]]++;
++M;
}
}
}
double mu = 0, scale = 1. / (M);
for (i = 0; i < N; i++)
mu += i*(double)h[i];
mu *= scale;
double mu1 = 0, q1 = 0;
double max_sigma = 0, max_val = 0;
for (i = 0; i < N; i++)
{
double p_i, q2, mu2, sigma;
p_i = h[i] * scale;
mu1 *= q1;
q1 += p_i;
q2 = 1. - q1;
if (std::min(q1, q2) < FLT_EPSILON || std::max(q1, q2) > 1. - FLT_EPSILON)
continue;
mu1 = (mu1 + i*p_i) / q1;
mu2 = (mu - q1*mu1) / q2;
sigma = q1*q2*(mu1 - mu2)*(mu1 - mu2);
if (sigma > max_sigma)
{
max_sigma = sigma;
max_val = i;
}
}
return max_val;
}
You then can wrap all in a function, here called threshold_with_mask, that wraps all different cases for you. If there is no mask, or the mask is all-white, then use cv::threshold. Otherwise, use one of the above mentioned approaches. Note that this wrapper works only for CV_8UC1 images (for simplicity sake, you can easily expand it to work with other types, if needed), and accepts all THRESH_XXX combinations as original cv::threshold.
double threshold_with_mask(Mat1b& src, Mat1b& dst, double thresh, double maxval, int type, const Mat1b& mask = Mat1b())
{
if (mask.empty() || (mask.rows == src.rows && mask.cols == src.cols && countNonZero(mask) == src.rows * src.cols))
{
// If empty mask, or all-white mask, use cv::threshold
thresh = cv::threshold(src, dst, thresh, maxval, type);
}
else
{
// Use mask
bool use_otsu = (type & THRESH_OTSU) != 0;
if (use_otsu)
{
// If OTSU, get thresh value on mask only
thresh = otsu_8u_with_mask(src, mask);
// Remove THRESH_OTSU from type
type &= THRESH_MASK;
}
// Apply cv::threshold on all image
thresh = cv::threshold(src, dst, thresh, maxval, type);
// Copy original image on inverted mask
src.copyTo(dst, ~mask);
}
return thresh;
}
Here is the full code for reference:
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
// Modified from thresh.cpp
// static double getThreshVal_Otsu_8u(const Mat& _src)
double otsu_8u_with_mask(const Mat1b src, const Mat1b& mask)
{
const int N = 256;
int M = 0;
int i, j, h[N] = { 0 };
for (i = 0; i < src.rows; i++)
{
const uchar* psrc = src.ptr(i);
const uchar* pmask = mask.ptr(i);
for (j = 0; j < src.cols; j++)
{
if (pmask[j])
{
h[psrc[j]]++;
++M;
}
}
}
double mu = 0, scale = 1. / (M);
for (i = 0; i < N; i++)
mu += i*(double)h[i];
mu *= scale;
double mu1 = 0, q1 = 0;
double max_sigma = 0, max_val = 0;
for (i = 0; i < N; i++)
{
double p_i, q2, mu2, sigma;
p_i = h[i] * scale;
mu1 *= q1;
q1 += p_i;
q2 = 1. - q1;
if (std::min(q1, q2) < FLT_EPSILON || std::max(q1, q2) > 1. - FLT_EPSILON)
continue;
mu1 = (mu1 + i*p_i) / q1;
mu2 = (mu - q1*mu1) / q2;
sigma = q1*q2*(mu1 - mu2)*(mu1 - mu2);
if (sigma > max_sigma)
{
max_sigma = sigma;
max_val = i;
}
}
return max_val;
}
double threshold_with_mask(Mat1b& src, Mat1b& dst, double thresh, double maxval, int type, const Mat1b& mask = Mat1b())
{
if (mask.empty() || (mask.rows == src.rows && mask.cols == src.cols && countNonZero(mask) == src.rows * src.cols))
{
// If empty mask, or all-white mask, use cv::threshold
thresh = cv::threshold(src, dst, thresh, maxval, type);
}
else
{
// Use mask
bool use_otsu = (type & THRESH_OTSU) != 0;
if (use_otsu)
{
// If OTSU, get thresh value on mask only
thresh = otsu_8u_with_mask(src, mask);
// Remove THRESH_OTSU from type
type &= THRESH_MASK;
}
// Apply cv::threshold on all image
thresh = cv::threshold(src, dst, thresh, maxval, type);
// Copy original image on inverted mask
src.copyTo(dst, ~mask);
}
return thresh;
}
int main()
{
// Load an image
Mat1b img = imread("D:\\SO\\img\\nice.jpg", IMREAD_GRAYSCALE);
// Apply OpenCV version
Mat1b cvth;
double cvth_value = threshold(img, cvth, 100, 255, THRESH_OTSU);
// Create a binary mask
Mat1b mask(img.rows, img.cols, uchar(0));
rectangle(mask, Rect(100, 100, 200, 200), Scalar(255), CV_FILLED);
// Apply threshold with a mask
Mat1b th;
double th_value = threshold_with_mask(img, th, 100, 255, THRESH_OTSU, mask);
// Show results
imshow("cv::threshod", cvth);
imshow("threshold_with_balue", th);
waitKey();
return 0;
}
来源：https://stackoverflow.com/questions/42432109/how-to-use-otsu-threshold-on-desired-range-of-a-histogram