I try to find the propability of a pixel from one image to belongs of the foreground and background of another image.
Therefore, I create 2 GMMs from one image with seperate foreground amd background (using a mask).
When I get back the log likelihood of the predict function, I have sometimes values >0 which is for me strange as the probability should be between 0 and 1. Is someone have experiment this kind of problem ?
Here is a test program showing the problem:
Mat mask = imread("mask.tiff", 0);
Mat formerImage = imread("ImageFormer.tiff");
Mat currentImage = imread("ImageCurrent.tiff");
// number of cluster in the GMM
int nClusters = 5;
int countB=0, countF=0;
Vec3b color;
Vec2d probFg, probBg; // probabilities to belong to the foreground or background from GMMs
//count the number of pixels for each training data
for(int c=0; c<=40;c++) {
for(int l=0; l<=40;l++) {
if(mask.at<BYTE>(l, c)==255) {
countF++;
} else if(mask.at<BYTE>(l, c)==0) {
countB++;
}
}
}
printf("countB %d countF %d \n", countB, countF);
Mat samplesForeground = Mat(countF,3, CV_64F);
Mat samplesBackground = Mat(countB,3, CV_64F);
// Expectation-Maximisation able to resolve the GMM and to predict the probability for a pixel to belong to the GMM.
EM em_foreground= EM(nClusters);
EM em_background= EM(nClusters);
countB=0;
countF=0;
// fill the training data from the former image depending of the mask
for(int c=0; c<=40;c++) {
for(int l=0; l<=40;l++) {
if(mask.at<BYTE>(l, c)==255) {
color = formerImage.at<Vec3b>(l, c);
samplesForeground.at<double>(countF,0)=color[0];
samplesForeground.at<double>(countF,1)=color[1];
samplesForeground.at<double>(countF,2)=color[2];
countF++;
} else if(mask.at<BYTE>(l, c)==0) {
color = formerImage.at<Vec3b>(l, c);
samplesBackground.at<double>(countB, 0)=color[0];
samplesBackground.at<double>(countB, 1)=color[1];
samplesBackground.at<double>(countB, 2)=color[2];
countB++;
}
}
}
printf("countB %d countF %d \n", countB, countF);
em_foreground.train(samplesForeground);
em_background.train(samplesBackground);
Mat sample(1, 3, CV_64F);
// try every pixel of the current image and get the log likelihood
for(int c=0; c<=40;c++) {
for(int l=0; l<=40;l++) {
color = currentImage.at<Vec3b>(l,c);
sample.at<double>(0)=color[0];
sample.at<double>(1)=color[1];
sample.at<double>(2)=color[2];
probFg=em_foreground.predict(sample);
probBg=em_background.predict(sample);
if(probFg[0]>0 || probBg[0]>0)
printf("probFg[0] %f probBg[0] %f \n", probFg[0], probBg[0]);
}
}
I tried the program with the followings images: