EconPapers    
Economics at your fingertips  
 

The Research on Image Extraction and Segmentation Algorithm in License Plate Recognition

Fang Weijian () and Xin Zhou ()
Additional contact information
Fang Weijian: Chongqing Three Gorges University
Xin Zhou: Chongqing Three Gorges University

A chapter in 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, 2013, pp 487-494 from Springer

Abstract: Abstract As a vital part of Intelligent Transportation System, License Plates Recognition System is meaningful in Vehicle Positioning and Traffic Monitoring. It consists of Vehicle License Plate Location, Character Segmentation and Character Recognition. In the paper we put forward a new method of segmentation algorithm on the basis of comparison and analysis some common methods of License Plate Recognition, which firstly chooses the self-adaptive thresholds for license images and executes the binarization; then arranges with projection Method and fixed-edge methods on the basis of connected-area methods. The experiment’s result shows this new method has better recognition performance.

Keywords: License plate recognition; Binarization; Image segmentation; Segmentation algorithm (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-34910-2_57

Ordering information: This item can be ordered from
http://www.springer.com/9783642349102

DOI: 10.1007/978-3-642-34910-2_57

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-02
Handle: RePEc:spr:sprchp:978-3-642-34910-2_57