Face image beautification is a widely used technique in multimedia

such as digital cameras

mobile terminals

advertising

and video conferences. However

several defects of face image beautification algorithms still exist today

such as the bad effects on detail-rich eyes and hair areas

as well as the poor visual effects on overall facial beautification images. A fast facial beautification method based on skin color segmentation and smoother face image is proposed in this study to overcome the defects of face beautification. First

based on characteristics of the skin's smoothness affecting facial attractiveness

facial blemishes are removed. The biexponential edge-preserving smoother is used to smooth the face image for facial defects and keep the important information of image edge. Second

some background information will be lost during the process of achieving skin smoothness

thereby making the separation of the skin and non-skin area a highly significant process. Then

based on the adaptive hue histogram

rapid detection

correction

and segmentation to the color region are achieved. Third

the mask has been obtained using the Gaussian fitting

which can have a box blur for many times for skin feather. Then

the skin feather is used to fuse the smoothed image and the original image to preserve the details of the face image

such as hair and background. Finally

based on the required white and natural skin as the beauty standard of a portrait

face image brightness is speedily adjusted

other important details are enhanced by fitting the log curve

and facial beautification can be achieved quickly. Compared with different methods of face image beautification

we performed qualitative and quantitative evaluation on the same face. After comparing with other facial beautification algorithms

we determined that the proposed algorithm in this study is more effective on the smoothness of edge-skin blemishes and has better ability to beautify the face image in terms of edge preservation; in terms of time complexity

its computing rate is 12 times as fast as the previous algorithms

and it ensures faster beautification of the face image relative to the previous images; in terms of operating methods

the proposed algorithm is simple

considering it only uses an adaptive histogram of chromatic channel to correct and segment skin color region

and it can achieve significant effect in color and non-color regions; and edge connection is more natural. We have performed a user study for the effectiveness of a proposed algorithm

beautifying a large number of face images with different genders

ages

poses

and backgrounds from the Internet. Experimental results show that the proposed algorithm has strong adaptive capacity because it can perfectly remove facial defects of most face images and it can simultaneously keep the background information unchanged

making the skin white and natural. The effectiveness of overall beautification is significant. In general

with its good beautification effect

the proposed algorithm obtains consistent high praise from many users. Specifically

it can moderately smooth the edges of the areas with many details

leaving no traces of an artificial process. The proposed algorithm with fast beautification of face image has a wide range of practicality.