Abstract
To improve the accuracy and efficiency of fabric design CAD, a wavelet-domain Markov model to image texture segmentation from a natural framework for intergrating both local and global information of jacquard fabric image behavior, together with contextual information.Firstly the Daubechies wavelet and tree-structure is selected, then the approach decomposes the low frequency part of the jacquard fabric image. Secondly within the theoretical framework of Markov random field, we construct the grey field distribution model and label field prior model with finite Gaussian mixture algorithm and multi-level logistic algorithm respectively. The experiments for almost 30 warp knitting jacquard fabric images show that this approach is a feasible way for jacquard fabric, and it supplies a theoretical platform for subsequent research.
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