Reflectance of human skin using colour photometric stereo: with particular application to pigmented lesion analysis.
OBJECTIVE
The optical appearance of human skin is highly dependent on the interaction between the illumination (type and position), observer position and the skin surface structure. Different currently available photographic techniques record different aspects of this appearance, each providing its own incomplete description. This limits their usefulness, especially for pigmented skin lesion diagnosis. In this paper a new, easy to use, low-cost photographic method is described,which aims to generate an efficiently encoded yet reasonably complete representation of skin appearance.


METHODS
A prototype hand-held camera was developed that rapidly acquires six colour images, each with the skin illuminated from a different direction. A novel photometric stereo processing was used to combine these into a colour image of the skin's diffuse reflectance, independent of the skin surface topography, as well as a separate representation of that topography in the form of a surface gradient image. Images of four clinical pigmented skin lesions were evaluated in comparison with conventional digital photographs by both visual judgement and automated lesion boundary detection.


RESULTS
The new colour reflectance images were free from the effects of topographical shading, shadowing and specular reflections. Lesion boundaries obtained automatically from the reflectance images were always closer to the outline drawn by a dermatologist than those obtained from conventional photographs. Finally, recombining the colour reflectance and surface gradient data to form a virtual image of the skin surface that is highly realistic in appearance.


CONCLUSIONS
The new colour photometric stereo camera produces images of skin and skin tumours in which the reflectance information that is related to subsurface pigment distribution is separated from the surface topographic information. The total information generated by the system, for use in visual or automated analysis, is potentially greater than that for either conventional photography or dermatoscopy alone. Its further development and broader clinical evaluation are warranted to determine its usefulness and role in a wide range of dermatological tasks, including tele-dermatology applications.
Sun
Jiuai
J
Machine Vision Laboratory, Faculty of CEMS, University of the West of England, Bristol, UK.
Smith
Melvyn
M
Smith
Lyndon
L
Coutts
Louise
L
Dabis
Rasha
R
Harland
Christopher
C
Bamber
Jeffrey
J
D003124:Colorimetry / Q000295:instrumentation / Q000379:methods*; D046169:Dermoscopy / Q000295:instrumentation / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D010780:Photogrammetry / Q000295:instrumentation / Q000379:methods*; D010783:Photometry / Q000295:instrumentation / Q000379:methods*; D010859:Pigmentation Disorders / Q000175:diagnosis* / Q000503:physiopathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012880:Skin Pigmentation; D012882:Skin Tests / Q000295:instrumentation / Q000379:methods