Video-based access control by automatic license plate recognition

被引：2

作者：

Di Nardo, Emanuel ^{[1
]}

Maddalena, Lucia ^{[2
]}

Petrosino, Alfredo ^{[1
]}

机构：

[1] University of Naples Parthenope, Department of Science and Technology, Naples

[2] National Research Council, Institute for High-Performance Computing and Networking, Naples

来源：

Smart Innovation, Systems and Technologies | 2015年 / 37卷

关键词：

Access control system; Automatic license plate recognition; Neural-based vehicle detection;

D O I：

10.1007/978-3-319-18164-6_11

中图分类号：

学科分类号：

摘要：

We report an access control system based on automatic license plate recognition, consisting of three main modules for acquisition, extraction, and recognition. The basic idea is to couple the online learning of a neural background model with a stopped foreground subtraction mechanism to efficiently provide a subset of relevant video frames where to look for. Another key point is the use of matching the entire license plate ROI with those stored in a database of authorized license plates, based on suitable features and validation tests. Experimental results confirm that the proposed system attains overall performance comparable with that of the state-of-the-art ALPR methods. © Springer International Publishing Switzerland 2015.

引用

页码：103 / 117

页数：14

共 29 条

[1]

Anagnostopoulos C.N., License plate recognition: A brief tutorial, IEEE Intelligent Transportation Systems Magazine, 6, 1, pp. 59-67, (2014)

[2]

Anagnostopoulos C.N., Anagnostopoulos I., Psoroulas I., Loumos V., Kayafas E., License plate recognition from still images and video sequences: A survey, IEEE Transactions on Intelligent Transportation Systems, 9, 3, pp. 377-391, (2008)

[3]

Ashtari A., Nordin M., Fathy M., An iranian license plate recognition system based on color features, IEEE Transactions on Intelligent Transportation Systems, (2014)

[4]

Bailey D., Irecki D., Lim B.K., Yang L., Test bed for number plate recognition applications, Proceedings of the First IEEE International Workshop on Electronic Design, Test and Applications, pp. 501-503, (2002)

[5]

Caner H., Gecim H., Alkar A., Efficient embedded neural-network-based license plate recognition system, IEEE Transactions on Vehicular Technology, 57, 5, pp. 2675-2683, (2008)

[6]

Chen Z.X., Liu C.Y., Chang F.L., Wang G.Y., Automatic license-plate location and recognition based on feature salience, IEEE Transactions on Vehicular Technology, 58, 7, pp. 3781-3785, (2009)

[7]

Comelli P., Ferragina P., Granieri M., Stabile F., Optical recognition of motor vehicle license plates, IEEE Transactions on Vehicular Technology, 44, 4, pp. 790-799, (1995)

[8]

Dasgupta S., Sinha K., Randomized partition trees for exact nearest neighbor search, Corr Abs/1302, (2013)

[9]

Dashtban M.H., Dashtban Z., Bevrani H., A novel approach for vehicle license plate localization and recognition, Int. J. Comput. Appl, 26, 11, pp. 22-30, (2011)

[10]

Dlagnekov L., Belongie S., Recognizing Cars, (2005)

← 1 2 3 →