TY - JOUR
T1 - Textile Image Segmentation Using a Multi-Resolution Markov Random Field Model on Variable Weights in the Wavelet Domain
AU - Junfeng Jing, Tao Peng & Pengfei Li
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.