A genetic algorithm based approach for combining binary image operators

Author(s)

Dornelles, Marta M. ; Hirata, Nina S. T. ; IEEE

• Document type: Journal article
• Source: 2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012); v. N/A, p. 4-pg., 2012-01-01.

Abstract

Combining several binary image operators, each one based on different windows, has proven to be an effective way to produce operators with better performance than designing single operators based on one window only. To facilitate the combination task that so far is done manually, we propose a genetic algorithm (GA) based approach. It consists of the definition of a collection of candidate windows and the use of a GA to select a subset of them that will determine the operators to be combined. Experimental results show that the proposed GA based approach produces combinations that are consistently better than those obtained manually, and indicate that the proposed window collections do contain relevant windows. (AU)

• FAPESP's process: 11/00325-1 - Challenges in multilevel design of morphological operators
• Grantee: Nina Sumiko Tomita Hirata
• Support Opportunities: Regular Research Grants