Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images

Most of the existing license plate (LP) detection systems have shown significant development in the processing of the images, with restrictions related to environmental conditions and plate variations. With increased mobility and internationalization, there is a need to develop a universal LP detect...

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Main Authors: Narasimha Reddy Soora, Parag S. Deshpande
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/9306282
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spelling doaj-50f5fdfa3ae446d3a3d4057480bf89122020-11-24T22:24:43ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/93062829306282Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still ImagesNarasimha Reddy Soora0Parag S. Deshpande1Department of Computer Science & Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, IndiaDepartment of Computer Science & Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, IndiaMost of the existing license plate (LP) detection systems have shown significant development in the processing of the images, with restrictions related to environmental conditions and plate variations. With increased mobility and internationalization, there is a need to develop a universal LP detection system, which can handle multiple LPs of many countries and any vehicle, in an open environment and all weather conditions, having different plate variations. This paper presents a novel LP detection method using different clustering techniques based on geometrical properties of the LP characters and proposed a new character extraction method, for noisy/missed character components of the LP due to the presence of noise between LP characters and LP border. The proposed method detects multiple LPs from an input image or video, having different plate variations, under different environmental and weather conditions because of the geometrical properties of the set of characters in the LP. The proposed method is tested using standard media-lab and Application Oriented License Plate (AOLP) benchmark LP recognition databases and achieved the success rates of 97.3% and 93.7%, respectively. Results clearly indicate that the proposed approach is comparable to the previously published papers, which evaluated their performance on publicly available benchmark LP databases.http://dx.doi.org/10.1155/2016/9306282
collection DOAJ
language English
format Article
sources DOAJ
author Narasimha Reddy Soora
Parag S. Deshpande
spellingShingle Narasimha Reddy Soora
Parag S. Deshpande
Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
Mathematical Problems in Engineering
author_facet Narasimha Reddy Soora
Parag S. Deshpande
author_sort Narasimha Reddy Soora
title Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
title_short Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
title_full Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
title_fullStr Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
title_full_unstemmed Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images
title_sort color, scale, and rotation independent multiple license plates detection in videos and still images
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description Most of the existing license plate (LP) detection systems have shown significant development in the processing of the images, with restrictions related to environmental conditions and plate variations. With increased mobility and internationalization, there is a need to develop a universal LP detection system, which can handle multiple LPs of many countries and any vehicle, in an open environment and all weather conditions, having different plate variations. This paper presents a novel LP detection method using different clustering techniques based on geometrical properties of the LP characters and proposed a new character extraction method, for noisy/missed character components of the LP due to the presence of noise between LP characters and LP border. The proposed method detects multiple LPs from an input image or video, having different plate variations, under different environmental and weather conditions because of the geometrical properties of the set of characters in the LP. The proposed method is tested using standard media-lab and Application Oriented License Plate (AOLP) benchmark LP recognition databases and achieved the success rates of 97.3% and 93.7%, respectively. Results clearly indicate that the proposed approach is comparable to the previously published papers, which evaluated their performance on publicly available benchmark LP databases.
url http://dx.doi.org/10.1155/2016/9306282
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AT paragsdeshpande colorscaleandrotationindependentmultiplelicenseplatesdetectioninvideosandstillimages
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