Abstract
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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Valdés-Vela, M., Herrero-Pérez, D., Martínez-Barberá, H. (2007). Towards Automatic Camera Calibration Under Changing Lighting Conditions Through Fuzzy Rules. In: Mira, J., Álvarez, J.R. (eds) Nature Inspired Problem-Solving Methods in Knowledge Engineering. IWINAC 2007. Lecture Notes in Computer Science, vol 4528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73055-2_40
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DOI: https://doi.org/10.1007/978-3-540-73055-2_40
Publisher Name: Springer, Berlin, Heidelberg
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