Set discrimination analysis tools for grey-level morphological operators

Robert C. Vogt III

doi:10.1117/12.46116

1 July 1991 Set discrimination analysis tools for grey-level morphological operators

Robert C. Vogt III

Author Affiliations +

Proceedings Volume 1568, Image Algebra and Morphological Image Processing II; (1991) https://doi.org/10.1117/12.46116
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

When considering ways to automate the generation of image processing algorithms for object recognition tasks, one critical element is the availability of measures to assess the potential and actual ability of individual operations for making a set of desired discriminations. This paper discusses the analysis and evaluation of grey-level image processing operators or algorithms from the perspective of trying to search automatically through a large space of them for one which satisfactorily performs a given recognition or discrimination task. Performance of an operator may be expressed in terms of accuracy, consistency, and cost, over an entire set of training images.The major issues of evaluating and choosing between operators in this context are discussed, and examples are given of measures which can be used to evaluate classes of operators for applicability, or to evaluate individual operators or parameter settings for actual performance. The paper first describes the form of the analysis for binary morphological operators, and then shows how it may be directly extended to grey-level morphological operators. Several examples are provided to show how grey-level pixel sets may be discriminated on the basis of various combinations of grey level and spatial criteria, as calculated by the basic morphological operators of erosion, dilation, opening, and closing.

Citation Download Citation

Robert C. Vogt III "Set discrimination analysis tools for grey-level morphological operators", Proc. SPIE 1568, Image Algebra and Morphological Image Processing II, (1 July 1991); https://doi.org/10.1117/12.46116

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