A rotation-invariant texture feature extraction method for tire pattern image
Yin Liu · 2015
A new image multi-scale texture feature extraction method with rotation invariance is proposed in order to improve the precision of tire pattern image.Curvelet transform is used to the tire pattern image to extract the mean and variance of each sub-band as the feature value.All feature values form a feature vector to represent the image texture features.The energy of each sub-band is calculated and sorted,and the feature vector with the largest energy feature value is recycling moved to the first place of the feature vector.Therefore the feature vector will not change with the image rotation.An experiment is carried out based on the tire pattern database.Experiment result shows that the precision of the proposed method is 47.5%,which is better than that of 35.5% and 41.17% by the wavelet transform algorithm and the curvelet transform algorithm respectively.