!7

// The relationship between the white and the black part in a traditional
// Haar-like feature could be much more general. Why do they have to
// touch each other? Why do they need to have the same aspect ratio?
// All we require is white area = black area so the subtraction makes sense.
//
// And even that could be lifted by applying a correction factor
// (area white / area black).
//
// Finally, they can even overlap, then you'd use a factor of
// (non-overlapping white area / non-overlapping black area).
// Or wait. Maybe the formula above is still correct.
//
// No idea if these would be called "generalized Haar features" or what
//
// The general unit returned by a Haar match should be pixels*brightness
// (value can be negative too).
//
// Result classification:
//   positive = match
//   0        = non-match (indifferent/not applicable)
//   negative = anti-match (Haar feature should be inverted)

srecord Haar(IIntegralImage img, DoubleRect rBlack, DoubleRect rWhite) {
  // Let's return a value between -1 (maximum anti-match) and
  // 1 (maximum match). Seems most elegant.
  
  double get() {
    double blackArea = area(rBlack);
    double whiteArea = area(rWhite);
    double factor = doubleRatio(whiteArea, blackArea);
    
    double whiteSum = img.pixelSum(rWhite); // this is between 0 and whiteArea*255
    double blackSum = img.pixelSum(rBlack); // this is between 0 and blackArea*255
    
    ret doubleRatio(whiteSum, whiteArea) - doubleRatio(blackSum, blackArea);
  }
}