A Multispectral Analysis of Black Skin Color Images for Linear Nigra Segmentation

dc.contributor.authorAZEHOUN-PAZOU, Géraud M.
dc.contributor.authorASSOGBA, KOKOU MARC
dc.contributor.authorADEGBI, HUGUES DANIEL GBADEBO
dc.date.accessioned2026-06-02T16:06:57Z
dc.date.available2026-06-02T16:06:57Z
dc.date.issued2017
dc.description.abstractLinea Nigra (LN) is a hyper pigmentation of skin which appear in men developing prostate cancer. Early diagnosis of such cancer can be made by image characterization. There generally exist low contrast between LN and surrounding areas in black skin images that influences segmentation accuracy. In this paper, this problem is addressed through a multi spectral analysis of RGB color images using Principal Component Analysis (PCA) method. This ledus to find the best component that ensure low loss of significant data when converting images from color to grayscale for segmentation purpose.The relevance of the proposed approach is demonstrated by results obtained in LN segmentation.
dc.identifier.otherBECDB-5656
dc.identifier.urihttps://dspace.uac.bj/handle/123456789/5230
dc.language.isofr
dc.relation.ispartofIEEE International Conference on Bio-Engineering for Smart Technologies (BioSmart2017)
dc.subjectMultispectral Analysis
dc.subjectPrincipal Component Analysis
dc.subjectSegmentation
dc.subjectLinea Nigra
dc.subjectBlack Skin Images.
dc.titleA Multispectral Analysis of Black Skin Color Images for Linear Nigra Segmentation
dc.typeArticle

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