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Proceedings Paper

Assessing facial wrinkles: automatic detection and quantification
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Paper Abstract

Nowadays, documenting the face appearance through imaging is prevalent in skin research, therefore detection and quantitative assessment of the degree of facial wrinkling is a useful tool for establishing an objective baseline and for communicating benefits to facial appearance due to cosmetic procedures or product applications. In this work, an algorithm for automatic detection of facial wrinkles is developed, based on estimating the orientation and the frequency of elongated features apparent on faces. By over-filtering the skin texture image with finely tuned oriented Gabor filters, an enhanced skin image is created. The wrinkles are detected by adaptively thresholding the enhanced image, and the degree of wrinkling is estimated based on the magnitude of the filter responses. The algorithm is tested against a clinically scored set of images of periorbital lines of different severity and we find that the proposed computational assessment correlates well with the corresponding clinical scores.

Paper Details

Date Published: 19 February 2009
PDF: 6 pages
Proc. SPIE 7161, Photonic Therapeutics and Diagnostics V, 71610J (19 February 2009); doi: 10.1117/12.811608
Show Author Affiliations
Gabriela O. Cula, Johnson &Johnson (United States)
Paulo R. Bargo, Johnson &Johnson (United States)
Nikiforos Kollias, Johnson &Johnson (United States)


Published in SPIE Proceedings Vol. 7161:
Photonic Therapeutics and Diagnostics V
Henry Hirschberg; Brian Jet-Fei Wong; Kenton W. Gregory; Reza S. Malek; Nikiforos Kollias; Bernard Choi; Guillermo J. Tearney; Justus F. R. Ilgner; Steen J. Madsen; Laura Marcu; Haishan Zeng, Editor(s)

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