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Using morphological operators and inpainting for hair removal in dermoscopic images

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21 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaCGI 2017 - Proceedings of the 2017 Computer Graphics International Conference
EditorialAssociation for Computing Machinery
ISBN (versión digital)9781450352284
DOI
EstadoPublicada - 27 jun 2017
Publicado de forma externa
Evento2017 Computer Graphics International Conference, CGI 2017 - Yokohama, Japón
Duración: 27 jun 201730 jun 2017

Serie de la publicación

NombreACM International Conference Proceeding Series
VolumenPart F128640

Conferencia

Conferencia2017 Computer Graphics International Conference, CGI 2017
País/TerritorioJapón
CiudadYokohama
Período27/06/1730/06/17

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