Paper Title:
Texture Segmentation of Jacquard Fabric Image Based on Multiresolution Markov Random Field
  Abstract

In order to develop an automated segmentation system for jacquard fabric images, a new approach based on MRMRF algorithm with variable weighing parameter is proposed in this paper. Firstly the variable weighting parameter different to the one in traditional MRMRF is described, which can provide a more accurate vector. The next step is MAP estimation and the model for texture segmentation. During this iterative process the initial value is big enough to learn more accurate parameters of feature energy. With the iterative number going on, the value will decrease and stop decreasing when the iterative number comes to some degree. Lastly the experiment results show that the new approach works better than the traditional method with constant weighing parameter.

  Info
Periodical
Chapter
Chapter 2: Simulation and Engineering Optimization
Edited by
Di Zheng, Yiqiang Wang, Yi-Min Deng, Aibing Yu and Weihua Li
Pages
496-499
DOI
10.4028/www.scientific.net/AMM.101-102.496
Citation
Y. C. Tong, Y. Zhang, J. Z. Yao, "Texture Segmentation of Jacquard Fabric Image Based on Multiresolution Markov Random Field", Applied Mechanics and Materials, Vols. 101-102, pp. 496-499, 2012
Online since
September 2011
Export
Price
$32.00
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