Rotation and gray-scale transform-invariant texture classification using spiral resampling, subband decomposition, and hidden Markov model

Wen-Rong Wu, Shieh-Chung Wei
1996 IEEE Transactions on Image Processing  
This paper proposes a new texture classification algorithm that is invariant to rotation and gray-scale transformation. First, we convert two-dimensional (2-D) texture images to onedimensional (1-D) signals by spiral resampling. Then, we use a quadrature mirror filter (QMF) bank to decompose sampled signals into subbands. In each band, we take high-order autocorrelation functions as features. Features in different bands, which form a vector sequence, are then modeled as a hidden Markov model
more » ... M). During classification, the unknown texture is matched against all the models and the best match is taken as the classification result. Simulations showed that the highest correct classification rate for 16 kinds of texture was 95.14%.
doi:10.1109/83.536891 pmid:18290060 fatcat:y2irjp5l65d4djce3pheom2j4u