DocumentCode
1566905
Title
Image Analysis Under Varying Illumination
Author
Zeng, Hengli ; Trussell, H.J.
Author_Institution
Dept. of Electr. & Comput. Eng., North Carolina Univ., Raleigh, NC, USA
fYear
2006
Firstpage
921
Lastpage
924
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.
Keywords
image sampling; learning (artificial intelligence); lighting; neural nets; hyperspectral image; image analysis; sample image; sample set; training data; varying illumination; Artificial neural networks; Hyperspectral imaging; Image analysis; Lighting; Neural networks; Neurons; Object detection; Pixel; Reflectivity; Vectors; Image processing; Lighting control; Neural network applications; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2006 IEEE International Conference on
Conference_Location
Atlanta, GA
ISSN
1522-4880
Print_ISBN
1-4244-0480-0
Type
conf
DOI
10.1109/ICIP.2006.312625
Filename
4106681
Link To Document