Automatic finding of optimal image processing for extracting concrete image cracks using features ACTIT

Authors

  • Haiying Bai,

    Non-member
    1. Graduate School of Environment and Information Sciences, Yokohama National University. 79-7, Tokiwadai, Hodogaya-ku Yokohama, Kanagawa 240-8501, Japan
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  • Noriko Yata,

    Non-member
    1. Graduate School of Environment and Information Sciences, Yokohama National University. 79-7, Tokiwadai, Hodogaya-ku Yokohama, Kanagawa 240-8501, Japan
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  • Tomoharu Nagao

    Member, Corresponding author
    1. Graduate School of Environment and Information Sciences, Yokohama National University. 79-7, Tokiwadai, Hodogaya-ku Yokohama, Kanagawa 240-8501, Japan
    • Graduate School of Environment and Information Sciences, Yokohama National University. 79-7, Tokiwadai, Hodogaya-ku Yokohama, Kanagawa 240-8501, Japan
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Abstract

In this paper, we autonomously define an optimal, efficient image-processing tree for extracting the cracks from concrete images using genetic programming (GP)-oriented evolutionary image processing known as Automatic Construction of Tree-structural Image Transformation (ACTIT). We propose the use of automatic finding feature from input and internal transformation images to optimize image-processing filters. These alternative solutions show significant improvements and can be performed by extracting small areas through our experimentation. This can possibly be used with an optimal image-processing system based on feature filters. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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