LineHoughTransform::LineHoughTransform(uint8_t *image, int m, int n, uint8_t gradientThreshold, uint8_t voteThreshold)
: image_(image), rows_(m), cols_(n), gradientThreshold_(gradientThreshold), voteThreshold_(voteThreshold)
{
maxDistance_ = static_cast<int>(std::sqrt((rows_-1)*(rows_-1)/4 + cols_*cols_));
accumulator_ = new uint8_t[maxDistance_*91];
// Zero the accumulator.
for(int i = 0; i < maxDistance_*91; ++i)
accumulator_[i] = 0;
edges_ = new uint8_t[rows_*cols_];
// Compute the brightness gradients for the image using the Sobel
// operator.
sobelEdgeDetect(image_, edges_, rows_, cols_);
}
float BlurDetect::calculateBlur(VImage* vim) {
QImage* image = vim->getQImage();
assert(image != NULL);
// Compute edges + histogram
QImage sobelEdges = sobelEdgeDetect(*image);
// vector<int> edgeStrengthHist = getEdgeHistogram(sobelEdges); // 15 bins
// float rating = calcBlurAmount(edgeStrengthHist);
// printHistogram(edgeStrengthHist);
vector<double> edgeStrengthList = getEdgeStrengthList(sobelEdges);
float rating2 = calcKurtosisRating(edgeStrengthList) * MAX_RATING;
// cerr << "Blur result: " << rating2 << endl;
return fmin(rating2, MAX_RATING);
}
