Using morphological operators and inpainting for hair removal in dermoscopic images

Julie Ann A. Salido, Conrado Ruiz

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

15 Cites (Scopus)


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 originalAnglès
Títol de la publicacióCGI 2017 - Proceedings of the 2017 Computer Graphics International Conference
EditorAssociation for Computing Machinery
ISBN (electrònic)9781450352284
Estat de la publicacióPublicada - 27 de juny 2017
Publicat externament
Esdeveniment2017 Computer Graphics International Conference, CGI 2017 - Yokohama, Japan
Durada: 27 de juny 201730 de juny 2017

Sèrie de publicacions

NomACM International Conference Proceeding Series
VolumPart F128640


Conferència2017 Computer Graphics International Conference, CGI 2017


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