Add integral image functionality to enable massive speedup of Sauvola

Note that there are some very small differences to the output compared
to the basic algorithm, but this doesn't make much difference.

This is due to minor differences with the standard deviation
calculation throughout, and with mean calculation at edges, for reasons
I'm unclear about.
WIP integral image speedup. mean is working

Very WIP, but mean is perfect once full window is used

Integral version all working!

Remove debugging info

Organise code better

1 files changed, 67 insertions, 0 deletions

diff --git a/binarize/util.go b/binarize/util.go
new file mode 100644
index 0000000..e7cf0f8
--- /dev/null
+++ b/binarize/util.go
@@ -0,0 +1,67 @@
+package main
+
+import (
+	"image"
+	"math"
+)
+
+func mean(i []int) float64 {
+	sum := 0
+	for _, n := range i {
+		sum += n
+	}
+	return float64(sum) / float64(len(i))
+}
+
+func stddev(i []int) float64 {
+	m := mean(i)
+
+	var sum float64
+	for _, n := range i {
+		sum += (float64(n) - m) * (float64(n) - m)
+	}
+	variance := sum / float64(len(i) - 1)
+	return math.Sqrt(variance)
+}
+
+func meanstddev(i []int) (float64, float64) {
+	m := mean(i)
+
+	var sum float64
+	for _, n := range i {
+		sum += (float64(n) - m) * (float64(n) - m)
+	}
+	variance := float64(sum) / float64(len(i) - 1)
+	return m, math.Sqrt(variance)
+}
+
+// gets the pixel values surrounding a point in the image
+func surrounding(img *image.Gray, x int, y int, size int) []int {
+	b := img.Bounds()
+	step := size / 2
+
+	miny := y - step
+	if miny < b.Min.Y {
+		miny = b.Min.Y
+	}
+	minx := x - step
+	if minx < b.Min.X {
+		minx = b.Min.X
+	}
+	maxy := y + step
+	if maxy > b.Max.Y {
+		maxy = b.Max.Y
+	}
+	maxx := x + step
+	if maxx > b.Max.X {
+		maxx = b.Max.X
+	}
+
+	var s []int
+	for yi := miny; yi <= maxy; yi++ {
+		for xi := minx; xi <= maxx; xi++ {
+			s = append(s, int(img.GrayAt(xi, yi).Y))
+		}
+	}
+	return s
+}