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Digital Assessment of Facial Acne Vulgaris

Malik, Aamir Saeed and Ramli, Roshaslinie and Hani, Ahmad Fadzil M and Salih, Yasir and Yap, Felix Boon-Bin and Nisar, Humaira (2014) Digital Assessment of Facial Acne Vulgaris. In: 2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014.

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Abstract

Acne affects 85% of adolescents at some time during their lives. Dermatologists use manual methods such as direct visual assessment and ordinary flash photography to assess the acne. However, these manual methods are time consuming and may result in intra-observer and inter-observer variations, even by experienced dermatologists. The objective of this research is to develop a computational imaging method for automated acne grading. The first step in the proposed method is pre-processing which involves lighting compensation. The CIE La*b* color space is used to measure any dissimilarity between skin colors. Acne segmentation has been performed using automated modified K-means clustering algorithm and support vector machines (SVM) classifier. Color and diameter are the main features extracted to classify acne blobs into different acne classes; papule, pustule, nodule or cyst. Finally, the severity level is determined such as mild, moderate, severe and very severe. Keywords-K-means clustering, SVM Classifier, Feature Extraction, Acne Grading System

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > Q Science (General)
T Technology > T Technology (General)
Academic Subject One:Bioimage processing
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Mission Oriented Research > Health
ID Code:11406
Deposited By: Dr Aamir Saeed Malik
Deposited On:28 Apr 2015 02:54
Last Modified:28 Apr 2015 02:54

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