An algorithm for accuracy enhancement of license plate recognition

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摘要

This paper presents an algorithm for extraction (detection) and recognition of license plates in traffic video datasets. For license plate detection, we introduce a method that applies both global edge features and local Haar-like features to construct a cascaded classifier consisting of 6 layers with 160 features. The characters on a license plate image are extracted by a method based on an improved blob detection algorithm for removal of unwanted areas. For license plate recognition (i.e., character recognition), an open source OCR is modified and used. Our proposed system is robust under poor illumination conditions and for moving vehicles. Our overall system is efficient and can be applied in real-time applications. Experimental results are demonstrated using a traffic video.

论文关键词:License plate detection,Statistical features,Haar-like features,Image segmentation,Blob detection algorithm,OCR

论文评审过程:Received 5 January 2011, Revised 14 November 2011, Accepted 1 May 2012, Available online 9 May 2012.

论文官网地址:https://doi.org/10.1016/j.jcss.2012.05.006