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.