#include "CHelpers.h" float* createEllipsoidKernel(Vec<size_t> radii, Vec<size_t>& kernelDims) { kernelDims = radii*2 +1; float* kernel = new float[kernelDims.product()]; memset(kernel,0,sizeof(float)*kernelDims.product()); Vec<int> mid((kernelDims-1)/2); Vec<float> dimScale = Vec<float>(1,1,1) / Vec<float>(radii.pwr(2)); Vec<int> cur(0,0,0); for (cur.z=0; cur.z<kernelDims.z; ++cur.z) { for (cur.y=0; cur.y<kernelDims.y; ++cur.y) { for (cur.x=0; cur.x<kernelDims.x; ++cur.x) { Vec<float> tmp = dimScale * Vec<float>((cur-mid).pwr(2)); if (tmp.x+tmp.y+tmp.z<=1.0f) { kernel[kernelDims.linearAddressAt(cur)] = 1.0f; } } } } return kernel; } 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; }