Automated Analysis of Scanning Electron Microscopic Images for Assessment of Hair Surface Damage

January 2020 in “ Royal Society Open Science ”

Fanny Chu, Deon S. Anex, A. Daniel Jones, Bradley R. Hart

scanning electron microscopy hair surface damage morphological damage explosive blasts tailing factor pixel brightness histograms surface roughness

TLDR A new automated method accurately measures hair damage using microscopic images.

The study focused on developing an automated method to analyze scanning electron microscopic images to assess hair surface damage. This approach aimed to provide a more efficient and objective evaluation of hair damage compared to traditional manual methods. The automated analysis was designed to identify and quantify surface irregularities and damage features on hair samples, potentially improving the accuracy and consistency of hair damage assessments. The research highlighted the potential of this technology to enhance the understanding of hair damage and improve the development of hair care products.

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