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Proceedings Paper

Biological tissue identification using a multispectral imaging system
Author(s): Céline Delporte; Sylvie Sautrot; Mohamed Ben Chouikha; Françoise Viénot; Georges Alquié
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Paper Abstract

A multispectral imaging system enabling biological tissue identifying and differentiation is presented. The measurement of β(λ) spectral radiance factor cube for four tissue types (beef muscle, pork muscle, turkey muscle and beef liver) present in the same scene was carried out. Three methods for tissue identification are proposed and their relevance evaluated. The first method correlates the scene spectral radiance factor with tissue database characteristics. This method gives detection rates ranging from 63.5 % to 85 %. The second method correlates the scene spectral radiance factor derivatives with a database of tissue β(λ) derivatives. This method is more efficient than the first one because it gives detection rates ranging from 79 % to 89 % with over-detection rates smaller than 0.2 %. The third method uses the biological tissue spectral signature. It enhances contrast in order to afford tissue differentiation and identification.

Paper Details

Date Published: 19 February 2013
PDF: 9 pages
Proc. SPIE 8659, Sensors, Cameras, and Systems for Industrial and Scientific Applications XIV, 86590H (19 February 2013); doi: 10.1117/12.2003033
Show Author Affiliations
Céline Delporte, Univ. Pierre et Marie Curie (France)
Sylvie Sautrot, Univ. Denis Diderot (France)
Univ. Pierre et Marie Curie (France)
Mohamed Ben Chouikha, Univ. Pierre et Marie Curie (France)
Françoise Viénot, Muséum National d'Histoire Naturelle (France)
Georges Alquié, Univ. Pierre et Marie Curie (France)


Published in SPIE Proceedings Vol. 8659:
Sensors, Cameras, and Systems for Industrial and Scientific Applications XIV
Ralf Widenhorn; Antoine Dupret, Editor(s)

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