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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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/9306282 |
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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 |
work_keys_str_mv |
AT narasimhareddysoora colorscaleandrotationindependentmultiplelicenseplatesdetectioninvideosandstillimages AT paragsdeshpande colorscaleandrotationindependentmultiplelicenseplatesdetectioninvideosandstillimages |
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1725760052911931392 |