Towards Automatic Camera Calibration Under Changing Lighting Conditions Through Fuzzy Rules
The context of this paper is the auto calibration of a CCD low cost camera of a robotic pet. The underlined idea of the auto calibration is to imitate the human eye capabilities, which is able to accommodates changing lighting conditions, and only when all functionalities works properly, light is co...
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Published in | Nature Inspired Problem-Solving Methods in Knowledge Engineering pp. 379 - 388 |
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Main Authors | , , |
Format | Book Chapter |
Language | English |
Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | The context of this paper is the auto calibration of a CCD low cost camera of a robotic pet. The underlined idea of the auto calibration is to imitate the human eye capabilities, which is able to accommodates changing lighting conditions, and only when all functionalities works properly, light is converted to impulses to the brain where the image is sensed. In order to choose the more appropriated camera’s parameters, a fuzzy rules model has been generated following a neuro-fuzzy approach. This model classifies images into five classes: from very dark, to very light. This is the first step to the generation of a subsequent fuzzy controller able to change the camera setting in order to improve the image received from an environment with changing lighting conditions. |
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ISBN: | 9783540730545 3540730540 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-540-73055-2_40 |