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Classification of Color Colposcopic Images by Neural Networks
Isabelle Claude
Renaud Winzenrieth
Philippe Pouletaut
Jean-Charles Boulanger
  DOI :  10.2352/CGIV.2002.1.1.art00083  Published Online :  January 2002
Abstract

This article presents colposcopic image classification based on color parameters used in a comparison study of different artificial neural networks and the knearest neighbors reference method. In this study, significant image data bases are used (617 images) from which two sets of parameters is extracted to characterize the attribute of color. More precisely, we select a set of color componants from color spaces based on data analysis and inner characteristics of different colposcopic image examinations. Experimental results show the feasibility of this study and the efficiency of the two sets of parameters since 90.9% of pink/red image set and 78% of brown/yellow image set have been correctly classified.

Journal Title : Conference on Colour in Graphics, Imaging, and Vision
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
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 DOI 10.2352/CGIV.2002.1.1.art00083
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Isabelle Claude, Renaud Winzenrieth, Philippe Pouletaut, Jean-Charles Boulanger, "Classification of Color Colposcopic Images by Neural Networks"  in Proc. IS&T CGIV 2002 First European Conf. on Colour in Graphics, Imaging, and Vision,  2002,  pp 394 - 397,  https://doi.org/10.2352/CGIV.2002.1.1.art00083

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Copyright © Society for Imaging Science and Technology 2002
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2158-6330(20020101)2002:1L.394;1-
cgiv_v2002n1/splitsection83.xml
/ist/cgiv/2002/00002002/00000001/art00083
Articles
Classification of Color Colposcopic Images by Neural Networks
ClaudeIsabelle
WinzenriethRenaud
PouletautPhilippe
BoulangerJean-Charles
01012002
2002
1
394
397
2002
This article presents colposcopic image classification based on color parameters used in a comparison study of different artificial neural networks and the knearest neighbors reference method. In this study, significant image data bases are used (617 images) from which two sets of parameters is extracted to characterize the attribute of color. More precisely, we select a set of color componants from color spaces based on data analysis and inner characteristics of different colposcopic image examinations. Experimental results show the feasibility of this study and the efficiency of the two sets of parameters since 90.9% of pink/red image set and 78% of brown/yellow image set have been correctly classified.