Jacquard image segmentation method based on fuzzy optimization technology

Authors:
Zhilin Feng;Jianwei Yin;Jiong Qiu;Xiaoming Liu;Jinxiang Dong
Affiliations:
,College of Zhijiang, Zhejiang University of Technology, Hangzhou, China;State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China;State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China;State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China;State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Year:
2005

Citing 4
Cited 0

Front propagation and phase field theory

SIAM Journal on Control and Optimization
Geometrical image segmentation by the Allen-Cahn equation

Applied Numerical Mathematics
A topology preserving level set method for geometric deformable models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture classification and segmentation using wavelet frames

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic pattern segmentation of jacquard images is a challenging task for jacquard pattern analysis. In this paper, the phase field model was introduced to extract specific pattern structures within jacquard images. A novel fuzzy optimization method, namely, Multi-start Fuzzy Optimization Method (MSFOM) was proposed for numerical solving of the phase field model. The proposed method was a hybrid algorithm combining fuzzy logic and genetic algorithms, which was able to find global minimum of the phase field model with low computational cost. Experimental results on synthetic and jacquard images demonstrate the efficacy of the proposed method.