Automatic Jordanian License Plate Recognition System Using Multistage Detection

Mustafa, Haneen Alhaj; Hassanin, Sara; Yaman, Musa Al

doi:10.1109/ssd.2018.8570408

Cited by 5 publications

(15 citation statements)

References 13 publications

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“…• The processing time for detecting the license plate and recognizing the plate numbers in both [12] and [13] was not reported at all, whereas in the proposed work it is being reported.…”

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confidence: 87%

“…In [13], the authors proposed a Jordanian ANPR system, where the license plate was detected and localized based on a multistage algorithm using the aspect ratio and the edges ratio. Back propagation neural network was used for recognizing the license plate characters (OCR).…”

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confidence: 99%

“…After surveying the literature and to the best of our knowledge, the work of [2,12,13] is the only published work that examines the detection and recognition of the license plates of the Jordanian vehicles. Therefore, the work presented in this paper extends the literature regarding the Jordanian license plates detection and recognition.…”

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confidence: 99%

“…Furthermore, the recognition of vehicle logo and make was also incorporated. It is worth mentioning the notes concerning the work by authors in [12] and [13]:…”

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confidence: 99%

“…• The dataset of [13] consisted of high resolution images withwww.astesj.com out presenting any sample images. In the proposed work many sample images are provided from the created and employed dataset, which mostly consisted of mid to low resolution images, but better than 320 × 240.…”

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confidence: 99%

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Automatic License Plate Detection and Recognition for Jordanian Vehicles

Yousef¹,

Mohd²,

Al-Khalaileh³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Jordanian license plates OCR (optical character recognition) rectangularity make of the vehicle Nowadays, automatic number plate recognition (ANPR) is very important especially in the era of smart cities and intelligent transport systems. Fully automated number plate detection and recognition system helps in reducing time, error, and cost for tracking of vehicles and for recording traffic violations. The main goal of this paper is to design a low cost fully automated number plate detection and recognition system targeting the Jordanian license plates. Several problems (e.g., cost, wasted efforts, manual intervention, and possible errors) were identified in the currently used Jordanian number plate recognition for recording traffic violations. We hope that the proposed system would mitigate such problems. The proposed system performs two main tasks. First, it automatically detects and recognizes the license plate number of a given Jordanian vehicle using a robust metric; the rectangularity measurement, and identifies the vehicle's type (e.g., governmental, private, visitor, public, etc.). Second, it recognizes a selected number of trained classes for the make of the vehicle whenever applicable. The experimentation results and the performance evaluations compared to other ANPR approaches show that proposed system achieves the best performance among the tested systems with a plate detection accuracy of 95%, OCR recognition accuracy of 94.68%, make recognition accuracy of 86.84%, and an overall ANPR accuracy of 89% excluding the make results.

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“…• The processing time for detecting the license plate and recognizing the plate numbers in both [12] and [13] was not reported at all, whereas in the proposed work it is being reported.…”

mentioning

confidence: 87%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…Furthermore, the recognition of vehicle logo and make was also incorporated. It is worth mentioning the notes concerning the work by authors in [12] and [13]:…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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