New neutrosophic approach to image segmentation

Authors:
Yanhui Guo;H. D. Cheng
Affiliations:
School of Computer Science and technology, Harbin, Institute of Technology, Harbin, 150001 China and Department of Computer Science, Utah State University, Logan, UT 84322, USA;School of Computer Science and technology, Harbin, Institute of Technology, Harbin, 150001 China and Department of Computer Science, Utah State University, Logan, UT 84322, USA
Venue:
Pattern Recognition
Year:
2009

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Abstract

Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. NS is a formal framework that has been recently proposed. However, NS needs to be specified from a technical point of view for a given application or field. We apply NS, after defining some concepts and operations, for image segmentation. The image is transformed into the NS domain, which is described using three membership sets: T, I and F. The entropy in NS is defined and employed to evaluate the indeterminacy. Two operations, @a-mean and @b-enhancement operations are proposed to reduce the set indeterminacy. Finally, the proposed method is employed to perform image segmentation using a @c-means clustering. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can segment the images automatically and effectively. Especially, it can segment the ''clean'' images and the images having noise with different noise levels.