NDLI: Extraction of Car License Plate Regions Using Line Grouping and Edge Density Methods

Content Provider	IEEE Xplore Digital Library
Author	Gisu Heo Minwoo Kim Insook Jung Duk-Ryong Lee Il-Seok Oh
Copyright Year	2007
Description	Author affiliation: Chonbuk Nat. Univ., Jeonju (Gisu Heo; Minwoo Kim; Insook Jung; Duk-Ryong Lee; Il-Seok Oh)
Abstract	In this paper we propose the double chance algorithm as an approach to car license plate extraction. The first algorithm extracts the line segments and groups them based on a set of geometrical conditions. It detects a rectangle at the plate boundary accurately. The second algorithm finds plate regions at which the vertical edges appear densest. We evaluated the double chance framework with and without the verification process. The verification process is performed using the character segmentation module. Using a real-life database collected by the speed enforcement camera, we obtained a high success rate of 99.45%, through use of the double chance approach with verification.
Starting Page	37
Ending Page	42
File Size	284446
Page Count	6
File Format	PDF
ISBN	0769530451
DOI	10.1109/ISITC.2007.79
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-23
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information science Image databases Image edge detection Roads Neural networks Licenses Cameras Character recognition Data mining Information technology
Content Type	Text
Resource Type	Article

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Extraction of Car License Plate Regions Using Line Grouping and Edge Density Methods