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
} }
Citation