|Table of Contents|

Object Confirmation Method Based on Principle Component Analysis and Its Application in Vehicle-logo Location and Recognition

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2009年01期
Page:
42-46
Research Field:
Publishing date:

Info

Title:
Object Confirmation Method Based on Principle Component Analysis and Its Application in Vehicle-logo Location and Recognition
Author(s):
WANG Mei12WANG Guo-hong1
1.Department of Electronic and Information Engineering,Naval Aeronautical Engineering Institute,Yantai 264001,China;2.Laboratory of Image Processing,Yantai Vocational College,Yantai 264670,China
Keywords:
principle component analysis plausibility function object confirmation vehicle-logo location and recognition
PACS:
TP391.41
DOI:
-
Abstract:
An object confirmation method based on principle component analysis(PCA)is presented to improve the accuracy of small object location and recognition.The object samples are regarded as a set of random vectors.A set of eigen-objects is given by PCA.The object reconstruction is executed by reflecting the located actual object to the eigen-space.The plausibility function is defined between original located object and reconstruction object and the function is used to confirm the true object or to delete the false object in order to reduce the false-alarm rate.Actual vehicle-logo images are used to test the method and the experiment shows that the accuracy of the object location is improved by 16.5 percent than the result without object confirmation.The invariant moment minimum distance classifier is used to complete the vehicle-logo recognition and the experiment result shows that the accuracy of the object recognition is improved by 20 percent.

References:

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Last Update: 2012-11-19