otsu.go

// Otsu is "A Threshold Selection Method from Gray-Level Histograms"
// <http://ieeexplore.ieee.org/ielx5/21/4310064/04310076.pdf?tp=&arnumber=4310076&isnumber=4310064>
func Otsu(hist []int, start, end int) int {
	if end == 0 {
		end = len(hist)
	} else if end >= len(hist) {
		end = len(hist) - 1
	}
	if start < 0 {
		start = 0
	} else if start >= len(hist) {
		start = len(hist) - 1
	}
	if start >= end {
		return (start + end) / 2
	}

	total := 0
	sum := 0
	for t := start; t < end; t++ {
		n := hist[t]
		total += n
		sum += t * n
	}

	sumB := 0
	wB := 0

	varMax := 0.0
	threshold := 0

	for t := start; t < end; t++ {
		wB += hist[t]
		if wB == 0 {
			continue
		}

		wF := total - wB
		if wF == 0 {
			break
		}

		sumB += t * hist[t]
		sumF := sum - sumB

		varBetween := float64(sumB*sumB)/float64(wB) + float64(sumF*sumF)/float64(wF)

		if varBetween > varMax {
			varMax = varBetween
			threshold = t
		}
	}
	return threshold
}


func HistogramLuminance(img image.Image) Histogram {
	bounds := img.Bounds()
	hist := make([]int, 256)

	if m, ok := img.(*image.RGBA); ok {
		w := bounds.Dx()
		h := bounds.Dy()
		for y, o := 0, 0; y < h; y, o = y+1, o+m.Stride {
			for x, o2 := 0, o; x < w; x, o2 = x+1, o2+4 {
				r := m.Pix[o2+0]
				g := m.Pix[o2+1]
				b := m.Pix[o2+2]
				max := r
				min := r
				if g > max {
					max = g
				}
				if g < min {
					min = g
				}
				if b > max {
					max = b
				}
				if b < min {
					min = b
				}
				hist[(int(max)+int(min))/2]++
			}
		}
	} else {
		for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
			for x := bounds.Min.X; x < bounds.Max.X; x++ {
				color := img.At(x, y)
				r, g, b, _ := color.RGBA()
				max := r
				min := r
				if g > max {
					max = g
				}
				if g < min {
					min = g
				}
				if b > max {
					max = b
				}
				if b < min {
					min = b
				}
				hist[((int(max)+int(min))/2)>>8]++
			}
		}
	}
	return hist
}