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Corner Detection Using Fuzzy Principles

Corner Detection Using Fuzzy Principles

Erik Cuevas, Daniel Zaldivar, Marco Perez-Cisneros
Copyright: © 2013 |Pages: 15
ISBN13: 9781466639942|ISBN10: 1466639946|EISBN13: 9781466639959
DOI: 10.4018/978-1-4666-3994-2.ch025
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MLA

Cuevas, Erik, et al. "Corner Detection Using Fuzzy Principles." Image Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2013, pp. 498-512. https://doi.org/10.4018/978-1-4666-3994-2.ch025

APA

Cuevas, E., Zaldivar, D., & Perez-Cisneros, M. (2013). Corner Detection Using Fuzzy Principles. In I. Management Association (Ed.), Image Processing: Concepts, Methodologies, Tools, and Applications (pp. 498-512). IGI Global. https://doi.org/10.4018/978-1-4666-3994-2.ch025

Chicago

Cuevas, Erik, Daniel Zaldivar, and Marco Perez-Cisneros. "Corner Detection Using Fuzzy Principles." In Image Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 498-512. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3994-2.ch025

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Abstract

Reliable corner detection is an important task in pattern recognition applications. In this chapter an approach based on fuzzy-rules to detect corners even under imprecise information is presented. The uncertainties arising due to various types of imaging defects such as blurring, illumination change, noise, et cetera. Fuzzy systems are well known for efficient handling of impreciseness. In order to handle the incompleteness arising due to imperfection of data, it is reasonable to model corner properties by a fuzzy rule-based system. The robustness of the proposed algorithm is compared with well known conventional detectors. The performance is tested on a number of benchmark test images to illustrate the efficiency of the algorithm in noise presence.

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