A Segmentation Algorithmfor Jacquard Images Based on Mumford-ShahModel

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dc.contributor.authorFeng, Z. L.en_US
dc.contributor.authorYin, J. W.en_US
dc.contributor.authorChen, G.en_US
dc.contributor.authorLiu, Yangen_US
dc.contributor.authorDong, J. X.en_US
dc.contributor.editorN. Correia and J. Jorge and T. Chambel and Z. Panen_US
dc.date.accessioned2014-01-26T16:16:45Z
dc.date.available2014-01-26T16:16:45Z
dc.date.issued2004en_US
dc.description.abstractAutomatic 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.en_US
dc.description.seriesinformationEurographics Multimedia Workshopen_US
dc.identifier.isbn3-905673-17-7en_US
dc.identifier.issn1812-7118en_US
dc.identifier.urihttps://doi.org/10.2312/EGMM/MM04/153-162en_US
dc.publisherThe Eurographics Associationen_US
dc.titleA Segmentation Algorithmfor Jacquard Images Based on Mumford-ShahModelen_US
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