Paper Info
Title
A Comparison on Histogram Based Image Matching Methods
Abstract
Using colour histogram as a stable representation over change in view has been widely used for object recognition. In this paper, three newly proposed histogram-based meth- ods are compared with other three popular methods, includ- ing conventional histogram intersection (HI) method, Wong and Cheung¿s merged palette histogram matching (MPHM) method, and Gevers¿ colour ratio gradient (CRG) method. These methods are tested on vehicle number plate images for number plate classification. Experimental results dis- close that, the CRG method is the best choice in terms of speed, and the GWHI method can give the best classifi- cation results. Overall, the CECH method produces the best performance when both speed and classification per- formance are concerned.
Year
DOI
Venue
2006
10.1109/AVSS.2006.5
AVSS
Keywords
Field
DocType
gwhi method,best choice,colour histogram,cech method,crg method,best classifi,popular method,best performance,conventional histogram intersection,merged palette histogram matching,histograms,object recognition,robustness,lighting,computer vision,helium,color
Histogram,Computer vision,Pattern recognition,Color histogram,Computer science,Histogram matching,Adaptive histogram equalization,Artificial intelligence,Balanced histogram thresholding,Image histogram,Histogram equalization,Color normalization
Conference
ISBN
Citations 
PageRank 
0-7695-2688-8
5
0.48
References 
Authors
8
4
Name
Order
Citations
PageRank
Wenjing Jia132545.08
Huaifeng Zhang224018.84
Xiangjian He3932132.03
Qiang Wu453454.06