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Vehicle image features extraction is a key problem for vehicle recognition and classification in the intelligent transportation system. The moment feature is often used as feature descriptors on vehicle types in the vehicle types extraction algorithm. Aiming at the great quantitative difference among the seven feature components of Hu moment and the disturbance from coefficient scale on them. Propose the feature extraction algorithm based on wavelet moment, lying on the principle of invariant moment and wavelet-energy. And the algorithm is applied on the vehicle image feature extraction. The real vehicle images are collected and pretreated in the experiment. After wavelet decomposition for the pretreatment images, the three-stage-subimages can be obtained, whose modified Hu moment also can be acquired through calculation. The modified moment is regarded as the feature. The result shows that the features extracted by the algorithm have the ability of keeping invariant after translation, rotation and scale transformation, which also could reflect the vital and essential attributes of target images and achieve the goals expected. Compared with the traditional Hu moments, recognition rate increased by 13.5%