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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
}
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