func main() {
file, strwidth, strheight, filter := parseArgs()
src := load(file)
width := realSize(src.Bounds().Dx(), strwidth)
height := realSize(src.Bounds().Dy(), strheight)
dst := scale.Resize(width, height, src, filter)
save(dst)
}
// Average computes a Perceptual Hash using a naive, but very fast method.
// It holds up to minor colour changes, changing brightness and contrast and
// is indifferent to aspect ratio and image size differences.
//
// Average Hash is a great algorithm if you are looking for something specific.
// For example, if we have a small thumbnail of an image and we wish to know
// if the big one exists somewhere in our collection. Average Hash will find
// it very quickly. However, if there are modifications -- like text was added
// or a head was spliced into place, then Average Hash probably won't do the job.
//
// The Average Hash is quick and easy, but it can generate false-misses if
// gamma correction or color histogram is applied to the image. This is
// because the colors move along a non-linear scale -- changing where the
// "average" is located and therefore changing which bits are above/below the
// average.
func Average(img image.Image) uint64 {
img = scale.Resize(8, 8, img, scale.NearestNeighbor)
img = grayscale(img)
mean := avgMean(img)
return avgHash(img, mean)
}
