Abstract: A new rotation invariant texture feature extraction method in the ridgelet transform domain is proposed. This method is that texture features are firstly extracted in every frequency subbands generated by 1-D wavelet transform in the ridgelet transform, and then relationship features between high frequency subband and low frequency subband in the same scale are extracted by constructing histogram, finally 1-D DFT is applied to above two types of features, and the amplitudes of Fourier coefficient are selected and fused using feature-level method, accordingly the rotation invariant texture features are attained. Experimental results show that the method proposed can achieve better classification performance comparing with another two existing methods.

Key words: computer application, texture classification, rotation invariance, ridgelet transform, feature extraction