Enhanced Detection and Evaluation of Facial Wrinkles Based on Image Denoising
Facial skin wrinkles are positively correlated with physiological age and are an important feature of aging.Existing wrinkle detection algorithms are influenced by facial features and image backgrounds,and can only detect specific regions of the face.Moreover,they focus heavily on the detection of horizontal forehead wrinkles,and suffer from inaccurate localization and identification of vertical or horizontal discontinuous textures as wrinkles,leading to low detection accuracy.In addition,in terms of wrinkle evaluation,existing methods or indicators cannot achieve quantitative evaluation of the overall wrinkles of the human face.To solve above problems,an enhanced facial wrinkle detection and evaluation method based on image denoising is pro-posed.Firstly,the facial image is preprocessed(denoised)using 2D-VMD to reduce the undesirable effects of non-wrinkled re-gions.Then,the hybrid Hessian filter is used to locate the wrinkle regions.Furthermore,the Dlib library is employed to elimi-nate facial features and image backgrounds,enabling wrinkle detection for the entire face.Finally,an improved quantitative evaluation method for wrinkles is proposed based on the geometric and intensity constraints of the wrinkle curve object.This method is not limited to the evaluation of a single wrinkle,which fills the gap in the quantitative evaluation of the overall facial wrinkles.The effectiveness of the proposed method is verified on representative 2D facial images of human faces.
万方数据
维普
