Abstract: The present invention provides a fast face beautifying method for digital images. Gaussian blur is performed to an original image to extract a green channel value which is then subject to linear light blending and hard light blending, and a blended green channel value is recalculated. Meanwhile, skin recognition and whitening are performed to the original image, and finally, by using a product of the recalculated green channel value by a probability obtained by skin recognition as a transparency, transparency blending is performed to the original image and the whitened image to compose a beautified image. Moreover, by performing skin recognition to the original image, black pixels will be prevented from being processing by an algorithm, so that hairs, eyes and other non skin parts will be prevented from being processing. Consequently, the final effect of beautification will become better and more natural.

Abstract: The present invention provides a fast face beautifying method for digital images. Gaussian blur is performed to an original image to extract a green channel value which is then subject to linear light blending and hard light blending, and a blended green channel value is recalculated. Meanwhile, skin recognition and whitening are performed to the original image, and finally, by using a product of the recalculated green channel value by a probability obtained by skin recognition as a transparency, transparency blending is performed to the original image and the whitened image to compose a beautified image. Moreover, by performing skin recognition to the original image, black pixels will be prevented from being processing by an algorithm, so that hairs, eyes and other non skin parts will be prevented from being processing. Consequently, the final effect of beautification will become better and more natural.