From 787d63fc5d13c6250bd33da5a8e1eadbe86188cd Mon Sep 17 00:00:00 2001
From: Nick White <git@njw.name>
Date: Tue, 8 Oct 2019 15:37:07 +0100
Subject: Continue separating the repository; remove all but preproc, and move
 integralimg package under it

---
 sauvola.go | 76 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 76 insertions(+)
 create mode 100644 sauvola.go

(limited to 'sauvola.go')

diff --git a/sauvola.go b/sauvola.go
new file mode 100644
index 0000000..3ba4359
--- /dev/null
+++ b/sauvola.go
@@ -0,0 +1,76 @@
+package preproc
+
+import (
+	"image"
+	"image/color"
+
+	"rescribe.xyz/preproc/integralimg"
+)
+
+// Implements Sauvola's algorithm for text binarization, see paper
+// "Adaptive document image binarization" (2000)
+func Sauvola(img *image.Gray, ksize float64, windowsize int) *image.Gray {
+	b := img.Bounds()
+	new := image.NewGray(b)
+
+	for y := b.Min.Y; y < b.Max.Y; y++ {
+		for x := b.Min.X; x < b.Max.X; x++ {
+			window := surrounding(img, x, y, windowsize)
+			m, dev := meanstddev(window)
+			threshold := m * (1 + ksize*((dev/128)-1))
+			if img.GrayAt(x, y).Y < uint8(threshold) {
+				new.SetGray(x, y, color.Gray{0})
+			} else {
+				new.SetGray(x, y, color.Gray{255})
+			}
+		}
+	}
+
+	return new
+}
+
+// Implements Sauvola's algorithm using Integral Images, see paper
+// "Efficient Implementation of Local Adaptive Thresholding Techniques Using Integral Images"
+// and
+// https://stackoverflow.com/questions/13110733/computing-image-integral
+func IntegralSauvola(img *image.Gray, ksize float64, windowsize int) *image.Gray {
+	b := img.Bounds()
+	new := image.NewGray(b)
+
+	integrals := integralimg.ToAllIntegralImg(img)
+
+	for y := b.Min.Y; y < b.Max.Y; y++ {
+		for x := b.Min.X; x < b.Max.X; x++ {
+			m, dev := integrals.MeanStdDevWindow(x, y, windowsize)
+			threshold := m * (1 + ksize*((dev/128)-1))
+			if img.GrayAt(x, y).Y < uint8(threshold) {
+				new.SetGray(x, y, color.Gray{0})
+			} else {
+				new.SetGray(x, y, color.Gray{255})
+			}
+		}
+	}
+
+	return new
+}
+
+// PreCalcedSauvola Implements Sauvola's algorithm using precalculated Integral Images
+// TODO: have this be the root function that the other two reference
+func PreCalcedSauvola(integrals integralimg.WithSq, img *image.Gray, ksize float64, windowsize int) *image.Gray {
+	b := img.Bounds()
+	new := image.NewGray(b)
+
+	for y := b.Min.Y; y < b.Max.Y; y++ {
+		for x := b.Min.X; x < b.Max.X; x++ {
+			m, dev := integrals.MeanStdDevWindow(x, y, windowsize)
+			threshold := m * (1 + ksize*((dev/128)-1))
+			if img.GrayAt(x, y).Y < uint8(threshold) {
+				new.SetGray(x, y, color.Gray{0})
+			} else {
+				new.SetGray(x, y, color.Gray{255})
+			}
+		}
+	}
+
+	return new
+}
-- 
cgit v1.2.1-24-ge1ad