Computational hair quality categorization in lower magnifications
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Raskar_Computational hair.pdf
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766.11 KB
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Author(s)
Heshmat Dehkordi, Barmak
Ikoma, Hayato
Lee, Ik Hyun
Rastogi, Krishna
Raskar, Ramesh
Date Issued
March 2015
Journal
Proceedings of SPIE--the Society of Photo-Optical Instrumentation Engineers
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Heshmat, Barmak et al. “Computational Hair Quality Categorization in Lower Magnifications.” Proceedings of SPIE, San Francisco, California, USA, 10 March, 2015. Vol. 9333., Edited by Adam Wax and Vadim Backman, SPIE, 2015. n.p. © 2015 SPIE
Version
Final published version
Abstract
We take advantage of human hair specific geometry to visualize sparse submicron cuticle peelings with highly oblique tip-side illumination. We show that the statistics of these features can directly estimate hair quality in much lower magnifications (down to 20x) with less powerful objectives when the features themselves are below the system resolution. Our technique has strong potential for lower cost, portable, and autonomous hair diagnostic apparatuses.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1117/12.2078027
