Auto Classification of Skin Symptom Based on Mahalanobis Distance

摘要：

A scheme for auto classification of skin symptom is introduced in this paper. It classifies different skin symptoms based on the principle of least Mahalanobis distance. Skin images with symptom to be identified will be preprocessed at first. Basic operations of preprocessing includes color space transformation, image segmentation based on threshold by self-adapting method, image post-processing by mathematical morphology, edge detection, contour tracing, seed filling and so on. After that, twenty-six characteristic parameters are extracted from symptom areas of the processed image. Calculate the distance between these parameters and the preset parameters of standard symptoms (chloasma, comedo, blackhead and ephelis), and we can classify the symptoms to certain category in accordance with their Mahalanobis distance in terms of the least difference principle.

关键词： machine vision Mahalanobis distance symptom classification image preprocessing

作者: Huijie JI Meihua Xu Feng Ran

作者单位: School of Mechatronical Engineering and AutomationShanghai UniversityShanghai, China Key Laboratory of Advanced Displays and system Application, Ministry of Education Shanghai Universit

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Advanced Computer Theory and Engineering(2010年第三届先进计算机理论与工程国际会议 ICACTE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）