The paper describes an innovative image annotation tool, based on a multi-class Support Vector Machine, for classifying image pixels in one of seven classes - sky, skin, vegetation, snow, water, ground, and man-made structures - or as unknown. These visual categories mirror high-level human perception, permitting the design of intuitive and effective color and contrast enhancement strategies. As a pre-processing step, a smart color balancing algorithm is applied, making the overall procedure suitable for uncalibrated images, such as images acquired by unknown systems under unknown lighting conditions.

Schettini, R., Gasparini, F., Cusano, C. (2005). Image annotation for adaptive enhancement of uncalibrated color images. In 8th International Conference on Visual Information Systems (pp.216-225). Springer [10.1007/11590064_19].

Image annotation for adaptive enhancement of uncalibrated color images

SCHETTINI, RAIMONDO;GASPARINI, FRANCESCA;CUSANO, CLAUDIO
2005

Abstract

The paper describes an innovative image annotation tool, based on a multi-class Support Vector Machine, for classifying image pixels in one of seven classes - sky, skin, vegetation, snow, water, ground, and man-made structures - or as unknown. These visual categories mirror high-level human perception, permitting the design of intuitive and effective color and contrast enhancement strategies. As a pre-processing step, a smart color balancing algorithm is applied, making the overall procedure suitable for uncalibrated images, such as images acquired by unknown systems under unknown lighting conditions.
poster + paper
image annotation, adaptive enhancement, uncalibrated color, SVM, pixel classification;
English
8th International Conference on Visual Information Systems (VISUAL 2005) - 5 July 2005 through 5 July 2005
2005
8th International Conference on Visual Information Systems
978-3-540-30488-3
2005
3736
216
225
none
Schettini, R., Gasparini, F., Cusano, C. (2005). Image annotation for adaptive enhancement of uncalibrated color images. In 8th International Conference on Visual Information Systems (pp.216-225). Springer [10.1007/11590064_19].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/13590
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