OpenCV threshold with mask
Solution 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;
}