Abstract
Color texture image segmentation is one of the fundamental task in image processing. For segmenting the color texture, we propose a new active contour model based on multichannel nonlocal and Tikhonov regularization. In the new model, nonlocal operator and Tikhonov regularization are simultaneously contributing to the evolutionary process of the active contour. The nonlocal operator which is based on the image slice similarity can direct the contour evolution on the boundary of the object and is not affected by the texture. The Tikhonov regularization can diffuse the texture areas and then accelerate the evolution process of the active contour. In order to ease the solution of the energy function, we also design the Split-Bregman algorithm of the proposed method. Expeimental color texture image segmentation results demonstrate the validity of the proposed method.
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Acknowledgments
This work was supported by National Natural Science Foundation of China (No.61305045), National “Twelfth Five-Year” development plan of science and technology (No.2013BAI01B03, No.2014BAG03B05).
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Wang, G., Lu, J., Pan, Z. et al. Color texture segmentation based on active contour model with multichannel nonlocal and Tikhonov regularization. Multimed Tools Appl 76, 24515–24526 (2017). https://doi.org/10.1007/s11042-016-4136-1
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DOI: https://doi.org/10.1007/s11042-016-4136-1