From e320e069844b8f9c6e5d7e4e407cc90dff3b0f04 Mon Sep 17 00:00:00 2001
From: Nick White <git@njw.name>
Date: Wed, 26 Feb 2020 16:53:14 +0000
Subject: Move things around so that integralimg is in its own repository

---
 sauvola.go | 80 --------------------------------------------------------------
 1 file changed, 80 deletions(-)
 delete mode 100644 sauvola.go

(limited to 'sauvola.go')

diff --git a/sauvola.go b/sauvola.go
deleted file mode 100644
index 5a9be03..0000000
--- a/sauvola.go
+++ /dev/null
@@ -1,80 +0,0 @@
-// Copyright 2019 Nick White.
-// Use of this source code is governed by the GPLv3
-// license that can be found in the LICENSE file.
-
-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
-}
-- 
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