Using morphological operators and inpainting for hair removal in dermoscopic images
© 2017 ACM. The increasing incidence of melanoma has led to development of computer-aided diagnosis systems that classify dermoscopic images. A fundamental problem however during the pre-processing stage is the removal of artifacts such as hair. Hair strands introduce additional edges, which can be...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2017
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| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/854 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1853/type/native/viewcontent |
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| Institution: | De La Salle University |
| Summary: | © 2017 ACM. The increasing incidence of melanoma has led to development of computer-aided diagnosis systems that classify dermoscopic images. A fundamental problem however during the pre-processing stage is the removal of artifacts such as hair. Hair strands introduce additional edges, which can be problematic when performing automatic skin lesion segmentation. This paper proposes a straightforward approach to automatic hair and consequently noise removal. The process starts with a median filter on each color space of RGB, a bottom hat filter, a binary conversion, a dilation and morphological opening, and then the removal of small connected pixels. The detected hair regions are then filled up using harmonic inpainting. Experiments were carried out on the PH2 datasets and compared to DullRazor. We also generated synthetic hair on skin images and measured the reconstruction quality using peak signal-to-noise ratio. |
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