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double* createEllipsoidKernel(Vec<size_t> radii, Vec<size_t>& kernelDims)
kernelDims.x = radii.x*2+1;
kernelDims.y = radii.y*2+1;
kernelDims.z = radii.z*2+1;
double* kernel = new double[kernelDims.product()];
memset(kernel,0,sizeof(double)*kernelDims.product());
mid.x = (kernelDims.x+1)/2;
mid.y = (kernelDims.y+1)/2;
mid.z = (kernelDims.z+1)/2;
Vec<float> dimScale(1.0f/((float)SQR(radii.x)),1.0f/((float)SQR(radii.y)),1.0f/((float)SQR(radii.z)));
if (dimScale.x*SQR(cur.x-mid.x)+dimScale.y*SQR(cur.y-mid.y)+dimScale.z*SQR(cur.z-mid.z)<=1)
int calcOtsuThreshold(const double* normHistogram, int numBins)
{
//code modified from http://www.dandiggins.co.uk/arlib-9.html
double totalMean = 0.0f;
for (int i=0; i<numBins; ++i)
totalMean += i*normHistogram[i];
double class1Prob=0, class1Mean=0, temp1, curThresh;
double bestThresh = 0.0;
int bestIndex = 0;
for (int i=0; i<numBins; ++i)
{
class1Prob += normHistogram[i];
class1Mean += i * normHistogram[i];
temp1 = totalMean * class1Prob - class1Mean;
curThresh = (temp1*temp1) / (class1Prob*(1.0f-class1Prob));
if(curThresh>bestThresh)
{
bestThresh = curThresh;
bestIndex = i;
}
}
return bestIndex;
}