License plate recognition from still images and video sequences: A survey

被引：349

作者：

Anagnostopoulos, Christos-Nikolaos E. ^{[1
]}

Anagnostopoulos, Ioannis E. ^{[2
]}

Psoroulas, Ioannis D. ^{[3
]}

Loumos, Vassili ^{[3
]}

Kayafas, Eleftherios ^{[3
]}

机构：

[1] Univ Aegean, Dept Cultural Technol & Commun, Mitilini 81100, Greece

[2] Univ Aegean, Dept Informat & Commun Syst Engn, Karlovassi 83200, Greece

[3] Natl Tech Univ Athens, Sch Elect & Comp Engn, Athens 15780, Greece

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2008年 / 9卷 / 03期

关键词：

image processing; license plate identification; license plate recognition (LPR); license plate segmentation; optical character recognition (OCR);

D O I：

10.1109/TITS.2008.922938

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页码：377 / 391

页数：15

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