Spectral analysis and unsupervised SVM classification for skin hyper-pigmentation classification

2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program

Volumn , Issue , 2010, Pages

  Prigent, Sylvain ^a   Descombes, Xavier ^a   Zugaj, Didier ^b   Zerubia, Josiane ^a  

^a UNIVERSITY OF NICE SOPHIA ANTIPOLIS   (France)

^b Galderma R and D   (France)

Author keywords

Data reduction; Projection pursuit; Skin hyper pigmentation; Spectral analysis; Support vector machine

Indexed keywords

AUTOMATIC METHOD; AUTOMATIC-LEARNING; HYPERSPECTRAL IMAGE ANALYSIS; MULTISPECTRAL IMAGES; PROJECTION PURSUITS; SPECTRAL ANALYSIS; SPECTRAL ANALYSIS METHOD; SUPERVISED CLASSIFICATION; SVM CLASSIFICATION;

GEARS; REMOTE SENSING; SIGNAL PROCESSING; SPECTRUM ANALYSIS; SPECTRUM ANALYZERS; STATISTICS; SUPPORT VECTOR MACHINES;

DATA REDUCTION;

EID: 78649296330     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WHISPERS.2010.5594917     Document Type: Conference Paper

References (9)

1. G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, "In vivo measurement of skin erythema and pigmentation: new means of implementation of diffuse reflectance spectroscopy with a commercial instrument," British Journal of Dermatology, vol. 159, pp. 683-690, 2008.
2. G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, "Non-invasive measurements of skin pigmentation in situ.," Pigment cell res, vol. 17, pp. 618-626, 2004.
3. S. Mallat and Z. Zhang, "Matching pursuit with time-frequency dictionaries," IEEE Trans. on Signal Processing, vol. 41, pp. 3397-3415, 1993.
4. L.O. Jimenez and D.A Landgrebe, "Hyperspectral data analysis and supervised feature reduction via projection pursuit," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, pp. 2653-2667, 1999.
5. G. Rellier, X. Descombes, F. Falzon, and J. Zerubia, "Texture feature analysis using a Gauss-Markov model in hyperspectral image classification," IEEE Trans. on Geoscience and Remote Sensing, vol. 42, pp. 1543-1551, 2004.
6. G. F. Hughes, "On the mean accuracy of statistical pattern recognizers," IEEE Trans. on Information Theory, vol. 14, pp. 55-63, 1968.
7. O. Zammit, X. Descombes, and J. Zerubia, "Burnt area mapping using support vector machines," International Conference on Forest Fire Research, Figueira da Foz, Portugal, 2006.
8. V. Vapnik, "Statistical learning theory," John Wiley and sons, inc., 1998.
9. M. Fauvel, "Spectral and spatial methods for the classification of urban remote sensing data," in PhD Thesis. Institut National Polytechnique de Grenoble. France, 2007.