Skin Type Classification using Machine Learning

• Main Author: Surenthran, Priyaganessri
• Format: Final Year Project
• Language: English
• Published: IRC 2020
• Subjects: Q Science (General)
• Online Access: http://utpedia.utp.edu.my/21703/1/24578_Priyaganessri%20Surenthran.pdf; http://utpedia.utp.edu.my/21703/

Skin is the largest organ of the body which protects us from microbes and helps to regulate body temperature. Skin types are determined by genetics. However, it can vary according to internal and external factors. Most people are not aware of their skin types and use multiple medication with no results. The identification of skin type has been controversial in the skincare industry because it is the primary factor to cure skin issue. Manual skin type identification has few drawbacks like human error and time consuming. The advancement of technology has made it easier to perform this diagnosis. However, most of the research on image classification only focuses on skin issues like acne, eczema and so on. There are very few which focuses on skin type classification. Even when that it requires large number of datasets. This research was done to analyse suitable method using image recognition and machine learning that can classify skin type with small number of datasets. It also evaluates proposed method to ensure it tackles the issue resulting in a testable prototype. The results obtained will be visualised using Rstudio to help user understand better. The methodology of this research would be data acquisition, pre-processing the data, image segmentation, classification and testing the model. As of for future work, the accuracy should be improved alongside number of datasets. The classification variety could be expanded as well.