An Integrative Approach to Accurate Vehicle Logo Detection
Vehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2013/391652 |
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| _version_ | 1832567787954896896 |
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| author | Hao Pan Bailing Zhang |
| author_facet | Hao Pan Bailing Zhang |
| author_sort | Hao Pan |
| collection | DOAJ |
| description | Vehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is
required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM), resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme. |
| format | Article |
| id | doaj-art-46c653df64a54d9b99971f4ec9679ba1 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-46c653df64a54d9b99971f4ec9679ba12025-02-03T01:00:31ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552013-01-01201310.1155/2013/391652391652An Integrative Approach to Accurate Vehicle Logo DetectionHao Pan0Bailing Zhang1Lucas Varity Langzhong Brake Co., Ltd, Langfang Development Zone, Hebei 065001, ChinaDepartment of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, SIP, Suzhou 215123, ChinaVehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM), resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.http://dx.doi.org/10.1155/2013/391652 |
| spellingShingle | Hao Pan Bailing Zhang An Integrative Approach to Accurate Vehicle Logo Detection Journal of Electrical and Computer Engineering |
| title | An Integrative Approach to Accurate Vehicle Logo Detection |
| title_full | An Integrative Approach to Accurate Vehicle Logo Detection |
| title_fullStr | An Integrative Approach to Accurate Vehicle Logo Detection |
| title_full_unstemmed | An Integrative Approach to Accurate Vehicle Logo Detection |
| title_short | An Integrative Approach to Accurate Vehicle Logo Detection |
| title_sort | integrative approach to accurate vehicle logo detection |
| url | http://dx.doi.org/10.1155/2013/391652 |
| work_keys_str_mv | AT haopan anintegrativeapproachtoaccuratevehiclelogodetection AT bailingzhang anintegrativeapproachtoaccuratevehiclelogodetection AT haopan integrativeapproachtoaccuratevehiclelogodetection AT bailingzhang integrativeapproachtoaccuratevehiclelogodetection |