A Novel Image Segmentation Algorithm Based on Fuzzy C-means Algorithm and Neutrosophic Set
Yanhui Guo 0, H.D. Cheng, Wei Zhao, Yingtao Zhang
0School of Computer Science and technology
Available Online December 2008.
- https://doi.org/10.2991/jcis.2008.44How to use a DOI?
- Image segmentation, fuzzy c-means, Neutrsophic set, Entropy.
- Image segment is an important step in image processing, pattern recognition and computer vision. Numerous algorithms have been proposed to in this field for last twenty years. However, a generalized segmentation method, especial for noisy image, are not studied greatly. A neutrosophic set (NS), a part of neu-trosophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a formal framework that has been recently pro-posed. However, the neutrosophic set needs to be specified from a technical point of view for a given application or field. We apply the neutrosophic set in image domain and define some concepts and operations for image segmentation. The image G is transformed into NS do-main. Then, the entropy in neutrosophic set is defined and employed to evaluate the indeterminancy. A new operation, -mean operation is proposed to reduce the set indeterminancy. Finally, a new fuzzy c-means algorithm, -fuzzy-c-means (-FCM) is proposed to segment the image on NS domain. We have conducted ex-periments on a variety of images. The ex-perimental results demonstrate that the proposed approach can segment the im-ages automatically and effectively. Espe-cially, it can process the “clean” images and the images with noise without know-ing its type, which is the most difficult task for image segmentation.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yanhui Guo AU - H.D. Cheng AU - Wei Zhao AU - Yingtao Zhang PY - 2008/12 DA - 2008/12 TI - A Novel Image Segmentation Algorithm Based on Fuzzy C-means Algorithm and Neutrosophic Set BT - 11th Joint International Conference on Information Sciences PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/jcis.2008.44 DO - https://doi.org/10.2991/jcis.2008.44 ID - Guo2008/12 ER -