A novel vehicle feature extraction algorithm based on wavelet moment

The moments of vehicle image features differ in magnitude and depend on the scale factor. To solve these problems, this paper proposes a feature extraction algorithm based on wavelet moment method. Focusing on the principles of invariant moment and wavelet energy, the proposed algorithm was applied to extract the features of pretreated images on actual vehicles. Specifically, the pretreated images were subjected to wavelet decomposition, yielding tertiary sub-images. Then, the sub-images were processed by taking the modified flu invariant moment as the feature. The results show that the features extracted by our algorithm remained invariant after translation, rotation and scale transformation, and reflected the vital and essential attributes of the vehicle images. The recognition rate of our algorithm was 13.5% higher than that of the traditional Hu moment. The research findings shed new light on image classification and recognition.