eprintid: 2754
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/27/54
datestamp: 2023-11-09 15:51:00
lastmod: 2023-11-09 15:51:00
status_changed: 2023-11-09 15:44:12
type: conference_item
metadata_visibility: show
creators_name: Hani, A.F.M.
creators_name: Prakasa, E.
creators_name: Nugroho, H.
creators_name: Affandi, A.M.
creators_name: Hussein, S.H.
title: Sample area for surface roughness determination of skin surfaces
ispublished: pub
keywords: 3D surface; Fitting error; High order polynomial; Input datas; Normal skin; Optimal performance; Rough surfaces; Roughness components; Roughness variation; sample area; Sample sizes; Skin surfaces, Algorithms; Dermatology; Skin, Surface roughness
note: cited By 5; Conference of 2012 4th International Conference on Intelligent and Advanced Systems, ICIAS 2012 ; Conference Date: 12 June 2012 Through 14 June 2012; Conference Code:93534
abstract: A surface roughness algorithm has been developed and validated for determining roughness of psoriasis lesions. The algorithm extracts an estimated waviness surface from 3D rough surface of psoriasis lesion by applying high order polynomial surface fitting. Vertical deviations of the lesion are determined by subtracting its 3D surface from the estimated waviness surface. However, the performance of the algorithm is dependent on the area of skin surface. The objective of this paper is to determine the minimum area for optimal performance of the skin surface roughness algorithm. In the determined sample area, all significant roughness components must be covered for surface roughness determination. To find the minimum size of sampled area, skin surface roughness has been determined at several sampling area variations. Normal skin surfaces are used as input data in this evaluation. By referring to the plot of surface roughness dependency on sampled area variation, it can be shown that the threshold area is found to be 4.9�4.9 mm 2 for skin surface roughness stability. Skin surface roughness variation is less for the sample areas larger than this threshold. However, there is a small surface roughness increment after the surface roughness stability. It is caused by fitting error at border regions of very large sample size. © 2012 IEEE.
date: 2012
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867938648&doi=10.1109%2fICIAS.2012.6306212&partnerID=40&md5=602c61fbc9347cae3ec9b0a12708110b
id_number: 10.1109/ICIAS.2012.6306212
full_text_status: none
publication: ICIAS 2012 - 2012 4th International Conference on Intelligent and Advanced Systems: A Conference of World Engineering, Science and Technology Congress (ESTCON) - Conference Proceedings
volume: 1
place_of_pub: Kuala Lumpur
pagerange: 328-332
refereed: TRUE
isbn: 9781457719677
citation:   Hani, A.F.M. and Prakasa, E. and Nugroho, H. and Affandi, A.M. and Hussein, S.H.  (2012) Sample area for surface roughness determination of skin surfaces.  In: UNSPECIFIED.