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2013 | OriginalPaper | Chapter

Genetic Programming for Automatic Construction of Variant Features in Edge Detection

Authors : Wenlong Fu, Mark Johnston, Mengjie Zhang

Published in: Applications of Evolutionary Computation

Publisher: Springer Berlin Heidelberg

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Basic features for edge detection, such as derivatives, can be further manipulated to improve detection performance. However, how to effectively combine different basic features remains an open issue and needs to be investigated. In this study, Genetic Programming (GP) is used to automatically and effectively construct rotation variant features based on basic features from derivatives,

F

-test, and histograms of images. To reduce computational cost in the training stage, the basic features only use the horizontal responses to construct new horizontal features. These new features are then combined with their own rotated versions in the vertical direction in the testing stage. The experimental results show that the rotation variant features constructed by GP combine advantages from the basic features, reduce drawbacks from basic features alone, and improve the detection performance.

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Metadata
Title
Genetic Programming for Automatic Construction of Variant Features in Edge Detection
Authors
Wenlong Fu
Mark Johnston
Mengjie Zhang
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-37192-9_36

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