@inproceedings{bad35ae737ef4736831fd9ad06633bbb,
title = "Color image segmentation by minimal surface smoothing",
abstract = "In this paper, we propose a two-stage approach for color image segmentation, which is inspired by minimal surface smoothing. Indeed, the first stage is to find a smooth solution to a convex variational model related to minimal surface smoothing. The classical primal-dual algorithm can be applied to efficiently solve the minimization problem. Once the smoothed image u is obtained, in the second stage, the segmentation is done by thresholding. Here, instead of using the classical K-means to find the thresholds, we propose a hill-climbing procedure to find the peaks on the histogram of u, which can be used to determine the required thresholds. The benefit of such approach is that it is more stable and can find the number of segments automatically. Finally, the experiment results illustrate that the proposed algorithm is very robust to noise and exhibits superior performance for color image segmentation.",
keywords = "Image segmentation, Minimal surface, Primal-dual method, Total variation",
author = "Zhi Li and Tieyong Zeng",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015 ; Conference date: 13-01-2015 Through 16-01-2015",
year = "2015",
doi = "10.1007/978-3-319-14612-6\_24",
language = "英语",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "321--334",
editor = "Xue-Cheng Tai and Egil Bae and Chan, \{Tony F.\} and Marius Lysaker",
booktitle = "Energy Minimization Methods in Computer Vision and Pattern Recognition - 10th International Conference,EMMCVPR 2015, Proceedings",
address = "德国",
}