Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/58629
Type: Artigo de periódico
Title: Quantitative analysis and classification of AFM images of human hair
Author: Gurden, SP
Monteiro, VF
Longo, E
Ferreira, MMC
Abstract: The surface topography of human hair, as defined by the outer layer of cellular sheets. termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the case of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density. allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.
Subject: atomic force microscopy
classification
cuticle
discriminant analysis
human hair
partial least squares
Country: Inglaterra
Editor: Blackwell Publishing Ltd
Rights: fechado
Identifier DOI: 10.1111/j.0022-2720.2004.01350.x
Date Issue: 2004
Appears in Collections:Unicamp - Artigos e Outros Documentos

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