@Article{JFBI-6-325, author = {}, title = {Textile Image Segmentation Using a Multi-Resolution Markov Random Field Model on Variable Weights in the Wavelet Domain}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2013}, volume = {6}, number = {3}, pages = {325--333}, abstract = {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.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi09201310}, url = {http://global-sci.org/intro/article_detail/jfbi/4846.html} }