Robust multiple car tracking with occlusion reasoning
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
An efficient implementation of the Hough transform for detecting vehicle license plates using DSP'S
RTAS '95 Proceedings of the Real-Time Technology and Applications Symposium
A Real Time Vehicle's License Plate Recognition System
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
A Real-Time Vehicle Detection and Tracking System in Outdoor Traffic Scenes
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
An efficient method of license plate location
Pattern Recognition Letters
Towards a Multinational Car License Plate Recognition System
Machine Vision and Applications
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Detecting, tracking and recognizing license plates
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Real-Time license plate detection under various conditions
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
Automatic license plate recognition
IEEE Transactions on Intelligent Transportation Systems
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We propose an efficient real-time automatic license plate recognition (ALPR) framework, particularly designed to work on CCTV video footage obtained from cameras that are not dedicated to the use in ALPR. At present, in license plate detection, tracking and recognition are reasonably well-tackled problems with many successful commercial solutions being available. However, the existing ALPR algorithms are based on the assumption that the input video will be obtained via a dedicated, high-resolution, high-speed camera and is/or supported by a controlled capture environment, with appropriate camera height, focus, exposure/shutter speed and lighting settings. However, typical video forensic applications may require searching for a vehicle having a particular number plate on noisy CCTV video footage obtained via non-dedicated, medium-to-low resolution cameras, working under poor illumination conditions. ALPR in such video content faces severe challenges in license plate localization, tracking and recognition stages. This paper proposes a novel approach for efficient localization of license plates in video sequence and the use of a revised version of an existing technique for tracking and recognition. A special feature of the proposed approach is that it is intelligent enough to automatically adjust for varying camera distances and diverse lighting conditions, a requirement for a video forensic tool that may operate on videos obtained by a diverse set of unspecified, distributed CCTV cameras.