Morphological feature-set optimization using the genetic algorithm

John M. Trenkle; Steven G. Schlosser; Robert C. Vogt III

doi:10.1117/12.46117

1 July 1991 Morphological feature-set optimization using the genetic algorithm

John M. Trenkle, Steven G. Schlosser, Robert C. Vogt III

Proceedings Volume 1568, Image Algebra and Morphological Image Processing II; (1991) https://doi.org/10.1117/12.46117
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

This paper is an investigation into the use of genetic algorithm techniques for doing optimal feature set selection in order to discriminate large sets of characters. Human experts defined a set of over 900 features from many different classes which could be used to help discriminate different characters from a chosen character set. Each of the features was assigned a cost, based on the average amount of CPU time necessary to compute it for a typical character. The goal of the task was to find the subset of features which produced the best trade-off between recognition accuracy and computational cost. The authors were able to show that by using all of the features or even major classes of them, high rates of discrimination accuracy for a printed character set (above 98% correct, first choice) could be obtained. Application of the genetic algorithm to selected subsets of characters and features demonstrated the ability of the method to significantly reduce the computational cost of the classification system and maintain or increase accuracy from the case where a complete set of features was used.

Citation Download Citation

John M. Trenkle, Steven G. Schlosser, and Robert C. Vogt III "Morphological feature-set optimization using the genetic algorithm", Proc. SPIE 1568, Image Algebra and Morphological Image Processing II, (1 July 1991); https://doi.org/10.1117/12.46117

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