Efficient two-level image thresholding method based on Bayesian formulation and the maximum entropy principle

Yan Chang; Alan M.N. Fu; Hong Yan; Mansuo Zhao

doi:10.1117/1.1501094

1 October 2002 Efficient two-level image thresholding method based on Bayesian formulation and the maximum entropy principle

Yan Chang, Alan M.N. Fu, Hong Yan, Mansuo Zhao

Author Affiliations +

Optical Engineering, Vol. 41, Issue 10, (October 2002). https://doi.org/10.1117/1.1501094

An efficient method for two-level thresholding is proposed based on the Bayes formula and the maximum entropy principle, in which no assumptions of the image histogram are made. An alternative criterion is derived based on maximizing entropy and used for speeding up the searching algorithm. Five forms of conditional probability distributions—simple, linear, parabola concave, parabola convex, and S-function—are employed and compared to each other for optimal threshold determination. The effect of precision on optimal threshold determination is discussed and a trade-off precision = 0.001 is selected experimentally. Our experiments demonstrate that the proposed method achieves a significant improvement in speed from 26 to 57 times faster than the exhaustive search method.

©(2002) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Yan Chang, Alan M.N. Fu, Hong Yan, and Mansuo Zhao "Efficient two-level image thresholding method based on Bayesian formulation and the maximum entropy principle," Optical Engineering 41(10), (1 October 2002). https://doi.org/10.1117/1.1501094

Published: 1 October 2002

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