A Morphological-Based License Plate Location

Faradji, Farhad; Rezaie, Amir Hossein; Ziaratban, Majid

doi:10.1109/icip.2007.4378890

Cited by 63 publications

(39 citation statements)

References 7 publications

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“…Edge detection methods are commonly used to find these rectangles [3] [4]. In [4], Sobel filter is used to detect edges. Candidate regions are generated in [2], by matching between vertical edges only.…”

Section: Fig 2: Block Diagram Of Anpr Systemmentioning

confidence: 99%

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Automatic Vehicle Number Plate Recognition System using Matlab

Tiwari¹,

Sharma²,

Singh³

et al. 2016

IOSR

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Section: Fig 2: Block Diagram Of Anpr Systemmentioning

confidence: 99%

“…Candidate regions are generated in [2], by matching between vertical edges only. In [4], the vertical edges are matched to obtain some candidate rectangles.…”

Section: Fig 2: Block Diagram Of Anpr Systemmentioning

confidence: 99%

Automatic Vehicle Number Plate Recognition System using Matlab

Tiwari¹,

Sharma²,

Singh³

et al. 2016

IOSR

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“…[1]The proposed histogram based analysis is suitable only if text is present in a straight line, whereas if the text is tilted or arranged in curves, it is quite difficult to locate it in full view. Edge based histogram analysis to locate license plate is proposed by [11]. Texture based method using frequency information like DCT is illustrated in [9].…”

Section: Introductionmentioning

confidence: 99%

Text Extraction from Complex Natural Images

Kumar¹,

Lee²

2010

International Journal of Contents

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“…In [1]- [4], [15] are real-time license plate recognition, and in [5]- [8], [16] are make a lot of ways the license plate location. In [1] use HSI color space method.…”

Section: Research Of Related Literaturementioning

confidence: 99%

Haar Discrete Wavelet-Based and Scanning Window for Vehicle License Plate Recognition

Lee¹,

Hung²

2017

JSW

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This paper is the study of vehicle license plate recognition. We use the scan window, 2-D Haar Discrete Wavelet Transform and Artificial Neural Networks. This paper consists of three main parts. First part is to locate and extract license plate. Second part is the Artificial Neural Network training of the license plate. Third part is a real time scans recognition. We use two times Haar Discrete Wavelet Transform image, and extract low frequency part LL of vehicles license plate image, makes image coefficient became original of one-sixteen, thus reducing image coefficients, so can to fast recognition.This method is to use scan the license plate recognition, but we do not license plate recognition for each character. Experiment result can be a high recognition rate.

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A Morphological-Based License Plate Location

Cited by 63 publications

References 7 publications

Automatic Vehicle Number Plate Recognition System using Matlab

Automatic Vehicle Number Plate Recognition System using Matlab

Text Extraction from Complex Natural Images

Haar Discrete Wavelet-Based and Scanning Window for Vehicle License Plate Recognition

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