Efficient evolutionary image processing using genetic programming: Reducing computation time for generating feature images of the Automatically Construction of Tree-Structural Image Transformation (ACTIT)

Using well-established techniques of Genetic Programming (GP), we automatically optimize image feature filters over several inputs and within transformation images, improving the Automatic Construction of Tree-Structural Image Transformation (ACTIT) system. Our objective is to also produce optimal s...

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Bibliographic Details
Published in2010 10th International Conference on Intelligent Systems Design and Applications pp. 302 - 307
Main Authors Haiying Bai, Yata, Noriko, Nagao, Tomoharu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2010
Subjects
computation time
evolutionary computing
feature filter
Filtering algorithms
Genetic programming
genetic programming (GP)
Image processing
Intelligent systems
Matched filters
Pixel
Training
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Summary:Using well-established techniques of Genetic Programming (GP), we automatically optimize image feature filters over several inputs and within transformation images, improving the Automatic Construction of Tree-Structural Image Transformation (ACTIT) system. Our objective is to also produce optimal solutions in substantially less computation time than require for generating features of ACTIT. We improved the algorithm feature filters in the process through GP, which are expressed by trees in Automatic Construction of Tree-Structural Image Transformation, to reduce computation time. Through our experimentation, we show that our new approach is accurate and requires less computation time by maintaining the feature images in conjunction with the original images.
ISBN:1424481341
9781424481347
ISSN:2164-7143
2164-7151
DOI:10.1109/ISDA.2010.5687249