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Bio-Inspired Polarization Vision Techniques for Robotics Applications

Bio-Inspired Polarization Vision Techniques for Robotics Applications

Abd El Rahman Shabayek, Olivier Morel, David Fofi
Copyright: © 2018 |Pages: 37
ISBN13: 9781522552048|ISBN10: 1522552049|EISBN13: 9781522552055
DOI: 10.4018/978-1-5225-5204-8.ch017
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MLA

Shabayek, Abd El Rahman, et al. "Bio-Inspired Polarization Vision Techniques for Robotics Applications." Computer Vision: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 421-457. https://doi.org/10.4018/978-1-5225-5204-8.ch017

APA

Shabayek, A. E., Morel, O., & Fofi, D. (2018). Bio-Inspired Polarization Vision Techniques for Robotics Applications. In I. Management Association (Ed.), Computer Vision: Concepts, Methodologies, Tools, and Applications (pp. 421-457). IGI Global. https://doi.org/10.4018/978-1-5225-5204-8.ch017

Chicago

Shabayek, Abd El Rahman, Olivier Morel, and David Fofi. "Bio-Inspired Polarization Vision Techniques for Robotics Applications." In Computer Vision: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 421-457. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5204-8.ch017

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Abstract

Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based visual behavior in the animal kingdom. Then, they go in depth with bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization-based techniques and how they are biologically inspired.

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