1.Department of Information and Engineering, College of Zhijiang, Zhejiang University of Technology, Hangzhou 310024,China；2. College of Information Technology, Zhejiang Vocational College of Commerce, Hangzhou 310053,China; 3. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China;
A novel motion texture detection algorithm based on the mixed state Markov random field (MRF) model was proposed to deal with the problem of low accuracy in defect detection of ink jet printing fabric under noisy environment. The representation of spatio temporal features was applied for motion texture. Meanwhile, a mixed state MRF model was introduced to constructing a feature map of motion texture, where motion and background states could be jointly modeled. Furthermore, a mixed state MRF detection model for motion texture was presented to enhance the capability representation of dynamic background texture changes. The process of motion texture detection was formulated into the feature energy minimization problem. A novel ICM optimization algorithm was employed to deal with the problem of simultaneous motion texture detection and dynamic background reconstruction to improve the detection accuracy of motion texture. The experimental results show that the proposed algorithm can effectively detect defect texture from ink jet printing fabric and has strong anti jamming ability against noise．
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