A Segmentation Algorithmfor Jacquard Images Based on Mumford-ShahModel
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Date
2004
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Automatic pattern segmentation of jacquard images is a challenging task due to the complexity of the images. Active contour models have become popular for finding the contours of a pattern with a complex shape. However, these models have many limitations on the pattern segmentation of jacquard images in the presence of noise. In this paper, a robust algorithm based on the Mumford-Shah model is proposed for the segmentation of noisy jacquard images. We discretize the Mumford-Shah model on piecewise lin-ear finite element spaces to yield greater stability and higher accuracy. A novel iterative relaxation algo-rithm for the numerical solving of the discrete version of the Mumford-Shah model is presented. During each iteration, we first refine and reorganize an adaptive triangular mesh to characterize the essential contour structure of a pattern. Then, we apply the quasi-Newton algorithm to find the absolute minimum of the discrete version of the model at the current iteration. Experimental results on synthetic and jac-quard images have shown the effectiveness and robustness of the algorithm.
Description
@inproceedings{10.2312:EGMM/MM04/153-162,
booktitle = {Eurographics Multimedia Workshop},
editor = {N. Correia and J. Jorge and T. Chambel and Z. Pan},
title = {{A Segmentation Algorithmfor Jacquard Images Based on Mumford-ShahModel}},
author = {Feng, Z. L. and Yin, J. W. and Chen, G. and Liu, Yang and Dong, J. X.},
year = {2004},
publisher = {The Eurographics Association},
ISSN = {1812-7118},
ISBN = {3-905673-17-7},
DOI = {10.2312/EGMM/MM04/153-162}
}