eprintid: 5001
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/50/01
datestamp: 2023-11-09 16:16:42
lastmod: 2023-11-09 16:16:42
status_changed: 2023-11-09 16:00:13
type: conference_item
metadata_visibility: show
creators_name: Malik, A.S.
creators_name: Ramli, R.
creators_name: Hani, A.F.M.
creators_name: Salih, Y.
creators_name: Yap, F.B.-B.
creators_name: Nisar, H.
title: Digital assessment of facial acne vulgaris
ispublished: pub
keywords: Color; Color photography; Dermatology; Feature extraction; Planning; Support vector machines; Sustainable development, Computational imaging; Flash photography; Grading system; K-means clustering; Lighting compensation; Modified k-means clustering; SVM classifiers; Visual assessments, Grading
note: cited By 14; Conference of 2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014 ; Conference Date: 12 May 2014 Through 15 May 2014; Conference Code:106826
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. © 2014 IEEE.
date: 2014
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905717229&doi=10.1109%2fI2MTC.2014.6860804&partnerID=40&md5=a0c1a386a45c07a6503f749b888e2a9a
id_number: 10.1109/I2MTC.2014.6860804
full_text_status: none
publication: Conference Record - IEEE Instrumentation and Measurement Technology Conference
place_of_pub: Montevideo
pagerange: 546-550
refereed: TRUE
isbn: 9781467363853
issn: 10915281
citation:   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.