Krishna Rastogi

Computational hair quality categorization in lower magnifications

Human hair specific geometry to visualize sparse submicron cuticle peelings with highly oblique tip-side illumination. We show that the statistics of the 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 for quality categorization of black, blond, and grey human scalp hair samples is successful in all cases. This technique has strong potential for lower cost, portable, and autonomous hair diagnostic apparatuses

B. Heshmat, H. Ikoma, I. H. Lee, K. Rastogi, R. Raskar, "Computational hair quality categorization in lower magnifications", Phot. West. SPIE. 9333-36, 2015

Team

Barmak Heshmat, IK Hyun Lee, Hayato Ikoma, Ramesh Raskar