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 methods are compared with other three popular methods, including 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 disclose that, the CRG method is the best choice in terms of
speed, and the GWHI method can give the best classification results. Overall, the CECH method produces the
best performance when both speed and classification performance are concerned.
