Abstract
This paper presents a three-dimensional level set-based image segmentation method. Instead of the typical image features, like intensity or edge information, the method uses texture feature analysis in order to be more applicable to image sets withs distinctive patterns. The current implementation makes use of a set of Grey Level Co-occurrence Matrix texture features that are generated and selected according to the characteristics of the initial region. The region is then deformed using the level set-based algorithm to cover the desired image area. The generation of the texture features and the level set surface deformation scheme are performed with graphics card hardware acceleration. The preliminary experiments, performed on synthetic data sets, show promising segmentation results.
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Acknowledgments
This work was supported by Bialystok University of Technology under Grant W/WI/5/2014 and S/WI/2/2013.
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Reska, D., Boldak, C., Kretowski, M. (2016). Toward Texture-Based 3D Level Set Image Segmentation. In: Choraś, R. (eds) Image Processing and Communications Challenges 7. Advances in Intelligent Systems and Computing, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-319-23814-2_24
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DOI: https://doi.org/10.1007/978-3-319-23814-2_24
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