Application of photometric stereo in dermatology
We adopted a computational approach to redesign a device that primarily inspects the skin for dermatological uses.
Our device is capable of capturing images of the skin, generating 3D views to display on a screen and analyse the images, to detect the presence of skin cancer - specifically malignant melanoma.
The device should be able to help experts differentiate between malignant melanoma and benign skin lesions.
We built and designed it at the CMV. The housing contains a camera and six LED light sources. A separate image is captured with each of the LEDs independently illuminated.
The photometric stereo stage of the algorithm is performed using the complete colour matrix equation.
The tool is used to inspect the skin via local or remote terminals. It produces images through a combination of photometric stereo, bump map generation and perspective projection.
Characterizing the skin by using images obtained with the device is an indispensable intermediate step in this project.
Good features extracted from geometric or colour information should be invariant or almost invariant to object position and pose, lighting condition and camera setup.
Features might include asymmetry, border, colour variation and diameter (ABCD).
Building a classifier combines several heuristic rules used by the dermatologists to identify malignant melanoma.
ABCD rules might be simple and inaccurate if treated separately. Although, combining them together using techniques like boosting, the final classifier would be highly accurate and has a good generalisation capability.
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Centre for Machine Vision is part of Bristol Robotics Laboratory, a centre of excellence in the Department of Engineering, Design and Mathematics at UWE Bristol.