| Titre |
A Multispectral Analysis of Black Skin Color Images for Linear Nigra Segmentation |
| Auteurs |
AZEHOUN-PAZOU Géraud M. [1],
ASSOGBA KOKOU MARC [2],
ADEGBI HUGUES DANIEL GBADEBO [3],
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| Journal: |
IEEE International Conference on Bio-Engineering for Smart Technologies (BioSmart2017) |
| Catégorie Journal: |
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| Impact factor: |
0 |
| Volume Journal: |
1 |
| DOI: |
978-1-5386-0706-0/17/IEEE |
| Resume |
Linea 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. |
| Mots clés |
Multispectral Analysis; Principal Component Analysis; Segmentation; Linea Nigra; Black Skin Images. |
| Pages |
27 - 30 |
| Fichier |
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