Data-driven color augmentation techniques for deep skin image analysis
Dermoscopic skin images are often obtained with different imaging devices, under varying
acquisition conditions. In this work, instead of attempting to perform intensity and color
normalization, we propose to leverage computational color constancy techniques to build an
artificial data augmentation technique suitable for this kind of images. Specifically, we apply
the\emph {shades of gray} color constancy technique to color-normalize the entire training
set of images, while retaining the estimated illuminants. We then draw one sample from the …
acquisition conditions. In this work, instead of attempting to perform intensity and color
normalization, we propose to leverage computational color constancy techniques to build an
artificial data augmentation technique suitable for this kind of images. Specifically, we apply
the\emph {shades of gray} color constancy technique to color-normalize the entire training
set of images, while retaining the estimated illuminants. We then draw one sample from the …
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