19 February 2009 Assessing facial wrinkles: automatic detection and quantification
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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.
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Gabriela O. Cula, Gabriela O. Cula, Paulo R. Bargo, Paulo R. Bargo, Nikiforos Kollias, Nikiforos Kollias, "Assessing facial wrinkles: automatic detection and quantification", Proc. SPIE 7161, Photonic Therapeutics and Diagnostics V, 71610J (19 February 2009); doi: 10.1117/12.811608; https://doi.org/10.1117/12.811608

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