A Fast Vertical Edge Detection Algorithm for Car License Plate Detection

Recently, License Plate Detection (LPD) has been used in many applications especially in transportation systems. Many methods have been proposed in order to detect license plates, but most of them worked under restricted conditions, such as fixed illumination, stationary background, and high reso...

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Main Author:	Ali Al-Ghaili, Abbas Mohammed
Format:	Thesis
Language:	English English
Published:	2009
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Online Access:	http://psasir.upm.edu.my/id/eprint/7316/1/FK_2009_28a.pdf
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spelling	my-upm-ir.73162013-05-27T07:34:37Z A Fast Vertical Edge Detection Algorithm for Car License Plate Detection 2009-07 Ali Al-Ghaili, Abbas Mohammed Recently, License Plate Detection (LPD) has been used in many applications especially in transportation systems. Many methods have been proposed in order to detect license plates, but most of them worked under restricted conditions, such as fixed illumination, stationary background, and high resolution images. LPD plays an important role in Car License Plate Recognition (CLPR) system because it affects the system's accuracy. This thesis aims to propose a fast vertical edge detector using Vertical Edge Detection Algorithm (VEDA) and to build a Car License Plate Detection (CLPD) method. Pre-processing step is performed in order to enhance and initialize the input image for the next steps. This step is divided into three processes: First, the color image conversion to a gray scale image. Second, an adaptive thresholding is used in order to constitute a binarized image. Third, Unwanted Lines Elimination Algorithm (ULEA) is used in order to enhance the image. The next step is to extract the vertical edges from the 352x288 resolution image by using VEDA. This algorithm is based on the contrast between the values in the binarized image. VEDA is proposed in order to enhance the CLPD method computation time. After the vertical edges have been extracted by VEDA, a morphological operation is used to highlight the vertical details in the image. Next, candidate regions are extracted. Finally, the license plate area is detected. This thesis shows that VEDA is faster than Sobel operator; the results reveal that VEDA is faster than Sobel by about 5-9 times, this range depends on the image resolution. The proposed CLPD method can efficiently detect the license plate area. The method shows the total time of processing one 352x288 image is 47.7 ms, and it meets the requirement of real time processing. Under the experiment datasets, which were taken from real scenes, 579 from 643 images are successfully detected. The average accuracy of car license plate detection is 90%. For more evaluation and comparison purposes, the proposed CLPD method is compared with a similar Malaysian license plate detection method, which is CAR Plate Extraction Technology (CARPET). This comparison reveled that the CLPD method is more efficient than CARPET and also has more detection rate. 2009-07 Thesis http://psasir.upm.edu.my/id/eprint/7316/ http://psasir.upm.edu.my/id/eprint/7316/1/FK_2009_28a.pdf application/pdf en public masters Universiti Putra Malaysia Faculty of Engineering English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
topic
spellingShingle	Ali Al-Ghaili, Abbas Mohammed A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
description	Recently, License Plate Detection (LPD) has been used in many applications especially in transportation systems. Many methods have been proposed in order to detect license plates, but most of them worked under restricted conditions, such as fixed illumination, stationary background, and high resolution images. LPD plays an important role in Car License Plate Recognition (CLPR) system because it affects the system's accuracy. This thesis aims to propose a fast vertical edge detector using Vertical Edge Detection Algorithm (VEDA) and to build a Car License Plate Detection (CLPD) method. Pre-processing step is performed in order to enhance and initialize the input image for the next steps. This step is divided into three processes: First, the color image conversion to a gray scale image. Second, an adaptive thresholding is used in order to constitute a binarized image. Third, Unwanted Lines Elimination Algorithm (ULEA) is used in order to enhance the image. The next step is to extract the vertical edges from the 352x288 resolution image by using VEDA. This algorithm is based on the contrast between the values in the binarized image. VEDA is proposed in order to enhance the CLPD method computation time. After the vertical edges have been extracted by VEDA, a morphological operation is used to highlight the vertical details in the image. Next, candidate regions are extracted. Finally, the license plate area is detected. This thesis shows that VEDA is faster than Sobel operator; the results reveal that VEDA is faster than Sobel by about 5-9 times, this range depends on the image resolution. The proposed CLPD method can efficiently detect the license plate area. The method shows the total time of processing one 352x288 image is 47.7 ms, and it meets the requirement of real time processing. Under the experiment datasets, which were taken from real scenes, 579 from 643 images are successfully detected. The average accuracy of car license plate detection is 90%. For more evaluation and comparison purposes, the proposed CLPD method is compared with a similar Malaysian license plate detection method, which is CAR Plate Extraction Technology (CARPET). This comparison reveled that the CLPD method is more efficient than CARPET and also has more detection rate.
format	Thesis
qualification_level	Master's degree
author	Ali Al-Ghaili, Abbas Mohammed
author_facet	Ali Al-Ghaili, Abbas Mohammed
author_sort	Ali Al-Ghaili, Abbas Mohammed
title	A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
title_short	A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
title_full	A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
title_fullStr	A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
title_full_unstemmed	A Fast Vertical Edge Detection Algorithm for Car License Plate Detection
title_sort	fast vertical edge detection algorithm for car license plate detection
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Engineering
publishDate	2009
url	http://psasir.upm.edu.my/id/eprint/7316/1/FK_2009_28a.pdf
_version_	1747810685942759424

A Fast Vertical Edge Detection Algorithm for Car License Plate Detection

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