摘要
面部皮肤皱纹与生理年龄呈正相关,是衰老的重要特征。现有的皱纹检测算法受人脸五官及图片背景影响,只能对面部局部区域进行检测,并且侧重于额头水平方向皱纹的检测,存在定位不准以及将垂直或水平不连续的纹理认定为皱纹的问题,从而导致皱纹检测准确率低。此外,在皱纹评价方面,现有方法缺乏对人脸整体皱纹的定量评价指标。为解决上述问题,提出一种基于图像去噪的面部皱纹增强检测及评价方法。首先,利用2D-VMD对人脸面部图像进行预处理去噪,降低非皱纹区域的不良影响;然后,使用混合Hessian滤波器定位皱纹区域,再利用Dlib库将人脸五官及图片背景去除,以实现对面部整体的皱纹检测;最后,根据皱纹曲线对象的几何约束及强度约束,提出一种改进的皱纹定量评价方法。该方法不再局限于对单条皱纹进行评价,填补了人脸整体皱纹定量评价指标的空缺。本文在二维人脸面部图像上验证了所提出的面部皱纹增强检测及评价方法的有效性。
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 proposed.Firstly,the facial image is preprocessed(denoised)using 2D-VMD to reduce the undesirable effects of non-wrinkled regions.Then,the hybrid Hessian filter is used to locate the wrinkle regions.Furthermore,the Dlib library is employed to eliminate 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.
作者
钟佳璇
郎恂
张宁涛
张曌
郭振宇
张梅
张榆锋
ZHONG Jiaxuan;LANG Xun;ZHANG Ningtao;ZHANG Zhao;GUO Zhenyu;ZHANG Mei;ZHANG Yufeng(Department of Electronic Engineering,Information School,Yunnan University,Kunming 650091,China;Yunnan Botanee Bio-technology Group Co.,Ltd.,Kunming 650091,China;Department of Dermatology,Kunming Children's Hospital,Kunming Medical University,Kunming 650100,China)
出处
《计算机与现代化》
2024年第10期35-41,共7页
Computer and Modernization
基金
国家自然科学基金资助项目(62261057,62201495)
云南大学第二届专业学位研究生实践创新项目(ZC-22221926)。
