Abstract
The paper presents two methods of creating custom color models used in object detection in digital images. Developed methods are based on Gram-Schmidt orthonormalization procedure and can be applied in different fields of recognition (human faces, remotely sensed images, etc.). Their main advantage over other ones is the efficient description and representation of color variations.
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© 2005 Springer Science+Business Media, Inc.
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Borawski, M., Forczmański, P. (2005). Gram-Schmidt Orthonormalization-Based Color Model for Object Detection. In: Saeed, K., Pejaś, J. (eds) Information Processing and Security Systems. Springer, Boston, MA. https://doi.org/10.1007/0-387-26325-X_9
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DOI: https://doi.org/10.1007/0-387-26325-X_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-25091-5
Online ISBN: 978-0-387-26325-0
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