The classification and recognition of the coke optical texture is one of the key elements to determine the quality and guide the production of cokes. As the results of the traditional methods in spatial and frequency domain are not so ideal

a fusion algorithm

which is based on WBCT and LBP

is proposed. Firstly

the method decomposes the coke micrograph with WBCT for multi-scale and multi-direction

and extracts the statistical features from each sub-band. Then in spatial domain

the features of coke micrograph are calculated with uniform LBP operator. Finally

according to the fusion similarity measure criteria

the classes of optical texture in coke micrograph are identified. Comparing with other methods

the results of experiments show that the proposed algorithm not only obtain a high recognition accuracy

but also has strong anti-interference ability

especially for the Poisson distribution of noise. Therefore

it is suitable for micrograph analysis of coke.