Color image segmentation based on neutrosophy

Ling Zhang; Ming Zhang; Heng-Da Cheng

doi:10.1117/1.OE.51.3.037009

6 April 2012 Color image segmentation based on neutrosophy

Ling Zhang, Ming Zhang, Heng-Da Cheng

Author Affiliations +

Optical Engineering, Vol. 51, Issue 3, 037009 (April 2012). https://doi.org/10.1117/1.OE.51.3.037009

Abstract

Neutrosophy studies the origin, nature, scope of neutralities, and their interactions with different ideational spectra. It is an alternative to the existing logics and represents mathematical uncertainty, vagueness, contradiction, and imprecision. Neutrosophy introduces a new concept to represent indeterminacy, which is a new philosophy to extend fuzzy logic. We introduce neutrosophy to color image segmentation and develop a novel unsupervised algorithm. We determine the centers of image clusters by using color information in red, green, and blue (RGB) color space and define neutrosophic indeterminacy by using spatial information in CIE (L*u*v*) color space. By applying neutrosophy, we integrate color and spatial information, as well as global and local information in two color spaces: RGB and CIE, respectively. Most existing segmentation algorithms have the over-segmentation problem, which causes segmentation accuracy to be lower, especially when noisy images are processed. Neutrosophy has noise-tolerant ability. In the experiment section, USC-SIPI image database is used to compare the proposed algorithm with several fuzzy and non-fuzzy color segmentation algorithms. The experiments demonstrate that the proposed algorithm can handle the segmentation tasks well and can even process noisy images with better accuracy. They also show its noise-tolerant ability. The proposed approach is more effective and powerful for color image segmentation, which can find wide applications in related areas.

Citation Download Citation

Ling Zhang, Ming Zhang, and Heng-Da Cheng "Color image segmentation based on neutrosophy," Optical Engineering 51(3), 037009 (6 April 2012). https://doi.org/10.1117/1.OE.51.3.037009

Published: 6 April 2012

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE