基于主动轮廓模型和振荡信息的无监督纹理分割

IF 1.2 Q2 MATHEMATICS, APPLIED
Guodong Wang, Zhenkuan Pan, Qian Dong, Ximei Zhao, Zhimei Zhang, J. Duan
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引用次数: 2

摘要

纹理经常出现在真实世界的图像中,并且可能在图像分割中造成相当大的困难。为了对纹理图像进行分割,提出了一种结合图像分解模型和活动轮廓模型的纹理图像分割模型。前一种模型能够从纹理图像中分离出结构分量和振荡分量,后一种模型能够提供平滑的分割轮廓。具体而言,我们只是将CCV(凸Chan-Vese)模型中的分段常数/光滑近似的数据项替换为图像分解模型- vo (Vese-Osher)的数据项。因此,我们提出的模型可以同时估计纹理图像的结构和振荡分量,并同时分割纹理。此外,我们还针对所提出的模型设计了快速的Split-Bregman算法。最后,通过对合成纹理图像和真实纹理图像的分割,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unsupervised Texture Segmentation Using Active Contour Model and Oscillating Information
Textures often occur in real-world images and may cause considerable difficulties in image segmentation. In order to segment texture images, we propose a new segmentation model that combines image decomposition model and active contour model. The former model is capable of decomposing structural and oscillating components separately from texture image, and the latter model can be used to provide smooth segmentation contour. In detail, we just replace the data term of piecewise constant/smooth approximation in CCV (convex Chan-Vese) model with that of image decomposition model-VO (Vese-Osher). Therefore, our proposed model can estimate both structural and oscillating components of texture images as well as segment textures simultaneously. In addition, we design fast Split-Bregman algorithm for our proposed model. Finally, the performance of our method is demonstrated by segmenting some synthetic and real texture images.
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来源期刊
Journal of Applied Mathematics
Journal of Applied Mathematics MATHEMATICS, APPLIED-
CiteScore
2.70
自引率
0.00%
发文量
58
审稿时长
3.2 months
期刊介绍: Journal of Applied Mathematics is a refereed journal devoted to the publication of original research papers and review articles in all areas of applied, computational, and industrial mathematics.
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