Dermoscopy, also called surface microscopy, is a non-invasive imaging procedure developed for early screening
of skin cancer. With recent advance in skin imaging technologies and image processing techniques, there has
been increasing interest in computer-aided diagnosis of skin cancer from dermoscopy images. Such diagnosis
requires the identification of over one hundred cutaneous morphological features. However, computer procedures
designed for extracting and classifying these intricate features can be distracted by the presence of artifacts like
hair, ruler markings, and air bubbles. Therefore, reliable artifact removal is an important pre-processing step for
improving the performance of computer-aided diagnosis of skin cancer. In this paper, we present a new scheme
that automatically detects and removes hairs and ruler markings from dermoscopy images. Moreover, our method
also addresses the issue of preserving morphological features during artifact removal. The key components of this
method include explicit curvilinear structure detection and modeling, as well as feature guided exemplar-based
inpainting. We experiment on a number of dermoscopy images and demonstrate that our method produces
superior results compared to existing techniques.
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