License Plate Recognition From Still Images and Video Sequences: A Survey

Распознавание номерных знаков на неподвижных изображениях и видеопоследовательностях: обзор
Ioannis Anagnostopoulos, Christos‐Nikolaos Anagnostopoulos, E. Kayafas, Ioannis Psoroulas, Vassili Loumos
2008-08-04

LPR image databasecharacter segmentationlicense plate recognitionoptical character recognitionplate localization
License plate recognition (LPR) algorithms in images or videos are generally composed of the following three processing steps: 1) extraction of a license plate region; 2) segmentation of the plate characters; and 3) recognition of each character. This task is quite challenging due to the diversity of plate formats and the nonuniform outdoor illumination conditions during image acquisition. Therefore, most approaches work only under restricted conditions such as fixed illumination, limited vehicle speed, designated routes, and stationary backgrounds. Numerous techniques have been developed for LPR in still images or video sequences, and the purpose of this paper is to categorize and assess them. Issues such as processing time, computational power, and recognition rate are also addressed, when available. Finally, this paper offers to researchers a link to a public image database to define a common reference point for LPR algorithmic assessment.
1
LPR is challenging due to diverse plate formats and nonuniform outdoor illumination during image acquisition.
2
LPR systems typically consist of three stages: plate region extraction, character segmentation, and character recognition.
3
Most LPR approaches operate only under restricted conditions (fixed illumination, limited vehicle speed, designated routes, stationary backgrounds).
4
The paper provides a link to a public image database to establish a common reference for LPR algorithm evaluation.
5
The survey categorizes and assesses numerous LPR techniques and discusses processing time, computational power, and recognition rate when available.

License plate images and video sequences (visual data containing vehicle license plates)

Algorithms and processing steps for license plate recognition including plate region extraction, character segmentation, character recognition, and evaluation metrics such as recognition rate, processing time, and computational requirements under varying plate formats and outdoor illumination

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2008-08-04
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Authors
Ioannis Anagnostopoulos
Christos‐Nikolaos Anagnostopoulos
E. Kayafas
Ioannis Psoroulas
Vassili Loumos
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