Department of Software Convergence, Graduate School, Soonchunhyang University, Asan, Chungnam, Republic of Korea.
Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Asan, Chungnam, Republic of Korea.
Skin Res Technol. 2022 Nov;28(6):815-826. doi: 10.1111/srt.13204. Epub 2022 Sep 28.
The skin surface becomes wrinkled and rough due to various internal and external factors. A three-dimensional (3D) analysis of the skin is required to improve skin conditions. Stereophotogrammetry, a noninvasive 3D analysis method, is easy to install and use, but most stereo systems have a fixed baseline and scale. Previous stereo systems are not suitable for observing micro-range skin features. Therefore, we suggest the optimal conditions and methods for the 3D analysis of skin microrelief using a multi-conditioned stereo system.
We constructed a nonconvergence model using a mobile device and acquired stereo images under multiscale and multi-baseline conditions. We extracted 3D information of the skin through our process: preprocessing, skin feature extraction, feature matching, and actual depth mapping. We improved the accuracy of the 3D analysis of the skin by using disparity values instead of disparity maps. We compared and analyzed the performances of six local feature detector and descriptor algorithms. In addition, we suggested depth-mapping formulas to estimate the actual depth of the skin microrelief.
We confirmed that stereo images with a working distance of 70-75 mm and a baseline of 4-8 mm are effective for the 3D analysis of skin microrelief. In addition, accelerated KAZE exhibited the best performance for features extraction and stereo matching. Finally, the extracted 3D information was converted to the actual depth, and the performance of the 3D analysis was verified.
The proposed system and method that provide texture information are effective for 3D skin disease analysis and evaluation.
皮肤表面会因各种内外因素变得起皱和粗糙。为了改善皮肤状况，需要对皮肤进行三维（3D）分析。立体摄影测量学是一种非侵入性的 3D 分析方法，易于安装和使用，但大多数立体系统都有固定的基线和比例。以前的立体系统不适合观察微范围的皮肤特征。因此，我们建议使用多条件立体系统对皮肤微起伏进行 3D 分析的最佳条件和方法。
我们使用移动设备构建了一个非收敛模型，并在多尺度和多基线条件下获取了立体图像。我们通过预处理、皮肤特征提取、特征匹配和实际深度映射等过程提取皮肤的 3D 信息。我们使用视差值而不是视差图来提高皮肤 3D 分析的准确性。我们比较和分析了六种局部特征检测器和描述符算法的性能。此外，我们还提出了深度映射公式来估计皮肤微起伏的实际深度。
我们证实了工作距离为 70-75mm、基线为 4-8mm 的立体图像对皮肤微起伏的 3D 分析有效。此外，加速 KAZE 在特征提取和立体匹配方面表现最佳。最后，提取的 3D 信息转换为实际深度，并验证了 3D 分析的性能。
所提出的提供纹理信息的系统和方法可有效用于 3D 皮肤疾病分析和评估。
