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Automatic finding of optimal image processing for extracting concrete image cracks using features ACTIT
Author(s) -
Bai Haiying,
Yata Noriko,
Nagao Tomoharu
Publication year - 2012
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21732
Subject(s) - image processing , computer science , artificial intelligence , transformation (genetics) , genetic programming , image (mathematics) , feature (linguistics) , computer vision , feature detection (computer vision) , tree (set theory) , pattern recognition (psychology) , genetic algorithm , digital image processing , feature extraction , machine learning , mathematics , mathematical analysis , biochemistry , chemistry , linguistics , philosophy , gene
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.