ICIP 2006, Atlanta, GA

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Paper Detail

Session:Machine Learning for Image and Video Classification
Time:Monday, October 9, 14:20 - 17:00
Presentation: Poster
Topic: Image & Video Storage and Retrieval: Machine Learning for image and video Classification
Authors: Huiwen Zeng; North Carolina State University 
 H. Joel Trussell; North Carolina State University 
Abstract: Often in dealing with images, the training data must be extracted for a limited data set. In particular, the illumination conditions of the sample images is limited and, in many cases, unknown. In this paper, we show that artificial variation of the illuminant of hyperspectral images can be used to overcome the limitations of a small sample set.