An Iranian License Plate Recognition System Based on Color Features

Ashtari, Amir Hossein; Nordin, Jan; Fathy, Mahmood

doi:10.1109/tits.2014.2304515

Cited by 150 publications

(48 citation statements)

References 24 publications

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“…The most popular approaches to this task are based on different models of neural networks, including artificial neural networks (ANNs) [27], probabilistic neural networks (PNNs) [54], and back propagation neural networks (BPNN) [83]. Within the category of machine learning methods, support vector machine (SVM) [18] -based approaches are also popular, as reported for example in [6]. Among other methods, template matching [77] and optical character recognition (OCR) [81] are also frequently used.…”

Section: Literature Reviewmentioning

confidence: 99%

A smart camera for the surveillance of vehicles in intelligent transportation systems

Baran

Ruść

Fornalski

2015

Multimed Tools Appl

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The paper presents a smart camera aimed at security and law enforcement applications for intelligent transportation systems. An extended background is presented first as a scholar literature review. The smart camera components and their capabilities for automatic detection and recognition of selected parameters of cars, as well as different aspects of the system efficiency, are described and discussed in detail in subsequent sections. Smart features of make and model recognition (MMR), license plate recognition (LPR) and color recognition (CR) are highlighted as the main benefits of the system. Their implementations, flowcharts and recognition rates are described, discussed and finally reported in detail. In addition to MMR, three different approaches, referred to as bag-of-features, scalable vocabulary tree and pyramid match, are also considered. The conclusion includes a discussion of the smart camera system efficiency as a whole, with an insight into potential future improvements.

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Section: Literature Reviewmentioning

confidence: 99%

A smart camera for the surveillance of vehicles in intelligent transportation systems

Baran

Ruść

Fornalski

2015

Multimed Tools Appl

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“…License Plate Recognition (LPR) by Optical Character Recognition (OCR) is an issue that is studied in Intelligent Transport Systems (ITS) and is important in intelligent infrastructure systems applications [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Numeric Character Recognition System for Chilean License Plates in semicontrolled scenarios

Olmí¹,

Urrea²,

Jamett³

2017

IJCIS

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The development of a computational tool for the recognition of numerical characters already segmented from Chilean license plates, located in semi-controlled scenarios, is presented. Two algorithms are highlighted: one for the Fine Segmentation of the Characters through the K-Means algorithm and a system of fuzzy logic; and a second one for the recognition through learning of the pseudo-real outline of the characters' skeleton a . The tool has an efficacy of 95 % and a processing time of 0.4 s.

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“…Vehicle license plate recognition is one of the most core technology in intelligent management system [2]. This technology used advanced computer image information processing and patterns recognition technology, to process the video data of traffic intersection and parking.…”

Section: Introductionmentioning

confidence: 99%

The research and design of vehicle license plate recognition system in traffic management system

Fu¹

2016

IJSIP

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An Iranian License Plate Recognition System Based on Color Features

Cited by 150 publications

References 24 publications

A smart camera for the surveillance of vehicles in intelligent transportation systems

A smart camera for the surveillance of vehicles in intelligent transportation systems

Numeric Character Recognition System for Chilean License Plates in semicontrolled scenarios

The research and design of vehicle license plate recognition system in traffic management system

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