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

---
 preproc/sauvola.go | 76 ------------------------------------------------------
 1 file changed, 76 deletions(-)
 delete mode 100644 preproc/sauvola.go

(limited to 'preproc/sauvola.go')

diff --git a/preproc/sauvola.go b/preproc/sauvola.go
deleted file mode 100644
index 046bb7d..0000000
--- a/preproc/sauvola.go
+++ /dev/null
@@ -1,76 +0,0 @@
-package preproc
-
-import (
-	"image"
-	"image/color"
-
-	"rescribe.xyz/go.git/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