TY - JOUR T1 - Textile Image Segmentation Using a Multi-Resolution Markov Random Field Model on Variable Weights in the Wavelet Domain JO - Journal of Fiber Bioengineering and Informatics VL - 3 SP - 325 EP - 333 PY - 2013 DA - 2013/06 SN - 6 DO - http://doi.org/10.3993/jfbi09201310 UR - https://global-sci.org/intro/article_detail/jfbi/4846.html KW - Texture KW - Image Segmentation KW - MRMRF Model KW - Wavelet Domain KW - Weight AB - This paper proposes a new texture image segmentation algorithm using a Multi-resolution Markov Random Field (MRMRF) model with a variable weight in the wavelet domain. For segmentation on textile printing design, firstly it combines wavelet decomposition to multi-resolution analysis. Secondly the energy of the label field and the feature field are calculated on multi-scales based on variable weight MRMRF algorithm. Finally new segmentation results are obtained and saved. Compared with traditional algorithms, experimental results prove that the new method presents a better performance in achieving the edge sharpness and similarity of results.