Abstract
Textures segmentation is a very important subject in the fields of computer vision. In order to segment the textures, a new method is achieved. The traditional Mumford-Shah model is modified. In detail, a smoothness term is added which used the nonlocal means method. The traditional Mumford-Shah model can be used to segment the conventional images. The modified Mumford-Shah model can dispose the textures well. What’s more, in order to improve the computation efficiency, this paper designs the Split-Bregman algorithm. At last, our performance is demonstrated by segmenting many real texture images.
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Lu, J., Wang, G., Pan, Z. (2015). The Modified Mumford-Shah Model Based on Nonlocal Means Method for Textures Segmentation. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48558-3_9
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DOI: https://doi.org/10.1007/978-3-662-48558-3_9
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