Physics Department, Politecnico di Torino, Torino, Italy.
Skin Res Technol. 2010 May;16(2):161-7. doi: 10.1111/j.1600-0846.2009.00413.x.
This paper discusses an image-processing method applied to skin texture analysis. Considering that the characterisation of human skin texture is a task approached only recently by image processing, our goal is to lay out the benefits of this technique for quantitative evaluations of skin features and localisation of defects.
We propose a method based on a statistical approach to image pattern recognition. The results of our statistical calculations on the grey-tone distributions of the images are proposed in specific diagrams, the coherence length diagrams.
Using the coherence length diagrams, we were able to determine grain size and anisotropy of skin textures. Maps showing the localisation of defects are also proposed.
According to the chosen statistical parameters of grey-tone distribution, several procedures to defect detection can be proposed. Here, we follow a comparison of the local coherence lengths with their average values. More sophisticated procedures, suggested by clinical experience, can be used to improve the image processing.
本文讨论了一种应用于皮肤纹理分析的图像处理方法。考虑到人类皮肤纹理的特征是图像处理最近才开始涉及的任务，我们的目标是阐述该技术在皮肤特征的定量评估和缺陷定位方面的优势。
我们提出了一种基于图像模式识别的统计方法。我们对图像灰度分布的统计计算结果以特定的图谱，即相干长度图谱的形式呈现。
使用相干长度图谱，我们能够确定皮肤纹理的粒度和各向异性。还提出了显示缺陷定位的图谱。
根据所选的灰度分布统计参数，可以提出几种缺陷检测程序。在这里，我们遵循局部相干长度与其平均值的比较。根据临床经验提出的更复杂的程序可以用于改进图像处理。
