期刊名称：International Journal of Reconfigurable Computing
印刷版ISSN：1687-7195
电子版ISSN：1687-7209
出版年度：2011
卷号：2011
DOI：10.1155/2011/712494
出版社：Hindawi Publishing Corporation
摘要：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.
