Image enhancement using fuzzy c-means clustering based on local population balance modeling

Duran, Necati; Catak, Muammer; Özbek, Melih

doi:10.1109/siu.2013.6531444

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2014

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“…The exact location of the license plate is extracted taking into consideration its dimensions. Readers may have a look at [8][9][10] for detailed information on fuzzy systems and fuzzy clustering.…”

Section: License Plate Locationmentioning

confidence: 99%

Car license plate recognition based on EKE-poisson transform

Catak

2014

Journal of Intelligent &Amp; Fuzzy Systems

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In this paper, a car license plate recognition (CLPR) system is presented. A CLPR system has three main subsystems such as; localization of the license plate in a given image; character segmentation of the license plate; recognition of the detected characters. Firstly, fuzzy c-means clustering is employed to determine the location of the license plate. Secondly, smearing algorithms (namely horizontal and vertical projections of the pixels of the license plate image) is used to carry out character segmentation. Finally, a novel Equipartition of Kinetic Energy (EKE)-Poisson transform is developed to recognize the characters. According to results, the proposed CLPR system is capable of supplying more than 92% of overall success rate.

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Section: License Plate Locationmentioning

confidence: 99%

Car license plate recognition based on EKE-poisson transform

Catak

2014

Journal of Intelligent &Amp; Fuzzy Systems

View full text Add to dashboard Cite

show abstract

Image enhancement using fuzzy c-means clustering based on local population balance modeling

Cited by 1 publication

References 6 publications

Car license plate recognition based on EKE-poisson transform

Car license plate recognition based on EKE-poisson transform

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