Johnson & Johnson Consumer Products Company, Skillman, NJ 08558, USA.
Skin Res Technol. 2013 Feb;19(1):e243-51. doi: 10.1111/j.1600-0846.2012.00635.x. Epub 2012 Jun 13.
As people mature, their skin gradually presents lines, wrinkles, and folds that become more pronounced with time. Skin wrinkles are perceived as important cues in communicating information about the age of the person. Nowadays, documenting the facial appearance through imaging is prevalent in skin research, therefore detection and quantitative assessment of the degree of facial wrinkling can be a useful tool for establishing an objective baseline and for assessing benefits to facial appearance due to various dermatological treatments. However, few image-based algorithms for computationally assessing facial wrinkles are present in the literature, and those that exist have limited reliability.
In this work, an algorithm for automatic detection of facial wrinkles is developed, based on estimating the orientation and the frequency of elongated spatial features, captured via digital image filtering.
The algorithm is tested against one set of clinically validated 11-point wrinkle scales present on the face. The algorithm is employed for assessing the presence of forehead furrows on a set of 100 clinically graded facial images. The proposed computational assessment correlates well with the corresponding clinical scores.
We find that the results are in better agreement with clinical scoring when the wrinkle depth information, approximated via filter responses, is combined with the wrinkle length information as opposed to the case when the two measures are considered separately.
随着人们的成熟，他们的皮肤逐渐出现线条、皱纹和褶皱，随着时间的推移，这些皱纹会变得更加明显。皮肤皱纹被认为是传达有关人年龄信息的重要线索。如今，通过成像记录面部外观在皮肤研究中很普遍，因此检测和定量评估面部皱纹的程度可以成为建立客观基线和评估各种皮肤病治疗对面部外观的益处的有用工具。然而，文献中很少有基于图像的算法可用于计算评估面部皱纹，并且那些现有的算法可靠性有限。
在这项工作中，开发了一种基于数字图像滤波捕获的细长空间特征的方向和频率估计的自动检测面部皱纹的算法。
该算法针对面部存在的一套经过临床验证的 11 分皱纹量表进行了测试。该算法用于评估 100 张临床分级面部图像上额部皱纹的存在。提出的计算评估与相应的临床评分高度相关。
我们发现，当通过滤波器响应近似的皱纹深度信息与皱纹长度信息相结合时，而不是当分别考虑这两个度量时，结果与临床评分更一致。
