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-rw-r--r--binarize/sauvola.go54
1 files changed, 0 insertions, 54 deletions
diff --git a/binarize/sauvola.go b/binarize/sauvola.go
deleted file mode 100644
index 6d9c1af..0000000
--- a/binarize/sauvola.go
+++ /dev/null
@@ -1,54 +0,0 @@
-package binarize
-
-import (
- "image"
- "image/color"
-)
-
-// 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)
-
- integral := Integralimg(img)
- integralsq := integralimgsq(img)
-
- for y := b.Min.Y; y < b.Max.Y; y++ {
- for x := b.Min.X; x < b.Max.X; x++ {
- m, dev := integralmeanstddev(integral, integralsq, 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
-}