Spatial object classification and recognition based on symmetric fuzzy relative entropy

Yufeng Shi; Jian Chen

doi:10.1117/12.867496

19 August 2010 Spatial object classification and recognition based on symmetric fuzzy relative entropy

Yufeng Shi, Jian Chen

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78200R (2010) https://doi.org/10.1117/12.867496
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

Based on fuzzy set theory, entropy, relative entropy and fuzzy entropy, the symmetric fuzzy relative entropy(SFRE) is presented, which not only has a full physical meaning, but also has succinct practicability. The symmetric fuzzy relative entropy can be used to measure the divergence between different fuzzy patterns. The example demonstrates that the symmetric fuzzy relative entropy is valid and reliable for spatial object recognition and classification, and its classification precision is very high.

Citation Download Citation

Yufeng Shi and Jian Chen "Spatial object classification and recognition based on symmetric fuzzy relative entropy", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78200R (19 August 2010); https://doi.org/10.1117/12.867496

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

Includes PDF, HTML & Video, when available