By Topic

A retrieval system of vehicles based on recognition of license plates

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xue-Chao Li ; Dept. of Comput. Sci., Xiamen Univ., Xiamen, China ; Cui-Hua Li ; Yi Xie

It is a laborious process for people to search vehicles from a large amount of video volumes. We build a retrieval system of vehicles using a novel method which recognizes license plate from surveillance videos. The core idea is to automatically convert video information into text information such that the tracing problem of vehicles can be simplified since all records of vehicles are efficiently managed by a well-designed vehicle database. Using a vehicle license plate as a key word, the retrieval system not only finds completed information of the vehicle but also visualizes the track of the vehicle by an electrical map. Firstly we propose a new algorithm to detect the key frames including vehicle license plate characters from video. The most important part is to distinguish vehicles from other objects. Secondly, we correct vehicle plates using modified Radon Transform. Thirdly, some necessary information about vehicles like time stamps is also recorded in the vehicles database. The experimental results show that the proposed algorithm is effective to deal with videos and record vehicles information. Text and visualization information which the database provides can meet users' requirements for searching vehicles.

Published in:

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on  (Volume:4 )

Date of Conference:

10-13 July 2011