Computational hair quality categorization in lower magnifications
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 t...
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Artikkeli |
| Kieli: | en_US |
| Julkaistu: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Linkit: | http://hdl.handle.net/1721.1/110721 https://orcid.org/0000-0003-0768-4815 https://orcid.org/0000-0002-3254-3224 |