Textile Image Segmentation Using a Multi-Resolution Markov Random Field Model on Variable Weights in the Wavelet Domain (Journal of Fiber Bioengineering and Informatics, 2013)
This paper proposes a new texture image segmentation algorithm using a Multi-resolution MarkovRandom Field (MRMRF) model with a variable weight in the wavelet domain. For segmentation ontextile printing design, firstly it combines wavelet decomposition to multi-resolution analysis. Secondlythe energy of the label field and the feature field are calculated on multi-scales based on variableweight MRMRF algorithm. Finally new segmentation results are obtained and saved. Compared withtraditional algorithms, experimental results prove that the new method presents a better performancein achieving the edge sharpness and similarity of results.
Keywords: Texture; Image Segmentation; MRMRF Model; Wavelet Domain; Weight