A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture
Joint Authors
Pedrino, Emerson Carlos
Roda, Valentin Obac
Saito, José Hiroki
Source
International Journal of Reconfigurable Computing
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-11-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Mathematical morphology supplies powerful tools for low-level image analysis.
Many applications in computer vision require dedicated hardware for real-time execution.
The design of morphological operators for a given application is not a trivial one.
Genetic programming is a branch of evolutionary computing, and it is consolidating as a promising method for applications of digital image processing.
The main objective of genetic programming is to discover how computers can learn to solve problems without being programmed for that.
In this paper, the development of an original reconfigurable architecture using logical, arithmetic, and morphological instructions generated automatically by a genetic programming approach is presented.
The developed architecture is based on FPGAs and has among the possible applications, automatic image filtering, pattern recognition and emulation of unknown filter.
Binary, gray, and color image practical applications using the developed architecture are presented and the results are compared with similar techniques found in the literature.
American Psychological Association (APA)
Pedrino, Emerson Carlos& Saito, José Hiroki& Roda, Valentin Obac. 2010. A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture. International Journal of Reconfigurable Computing،Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-492534
Modern Language Association (MLA)
Pedrino, Emerson Carlos…[et al.]. A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture. International Journal of Reconfigurable Computing No. 2011 (2011), pp.1-10.
https://search.emarefa.net/detail/BIM-492534
American Medical Association (AMA)
Pedrino, Emerson Carlos& Saito, José Hiroki& Roda, Valentin Obac. A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture. International Journal of Reconfigurable Computing. 2010. Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-492534
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-492534