relation: https://khub.utp.edu.my/scholars/5001/
title: Digital assessment of facial acne vulgaris
creator: Malik, A.S.
creator: Ramli, R.
creator: Hani, A.F.M.
creator: Salih, Y.
creator: Yap, F.B.-B.
creator: Nisar, H.
description: 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. © 2014 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2014
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Malik, A.S. and Ramli, R. and Hani, A.F.M. and Salih, Y. and Yap, F.B.-B. and Nisar, H.  (2014) Digital assessment of facial acne vulgaris.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905717229&doi=10.1109%2fI2MTC.2014.6860804&partnerID=40&md5=a0c1a386a45c07a6503f749b888e2a9a
relation: 10.1109/I2MTC.2014.6860804
identifier: 10.1109/I2MTC.2014.6860804