Soft Edge Maps From Edge Detectors Evolved by Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Fu:2012:CEC,
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title = "Soft Edge Maps From Edge Detectors Evolved by Genetic
Programming",
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author = "Wenlong Fu and Mark Johnston and Mengjie Zhang",
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pages = "1356--1363",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6256105",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Conflict of
Interest Papers, Evolutionary Computer Vision,
Evolutionary programming",
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abstract = "Genetic Programming (GP) has been used for edge
detection, but there is no previous work that analyses
the outputs from a GP detector before thresholding them
to binary edge maps. When the threshold used in a GP
system slightly changes, the final edge map from a
detector may change a lot. Mapping the outputs of a GP
detector to a grayscale space by a linear
transformation is not effective. In order to address
the problem of the sensitivity to the threshold values,
we replace the linear transformation with an S-shaped
transformation. We design two new fitness functions so
that the outputs from an evolved detector can obtain
better edge maps after mapping into a grayscale space.
Experimental results show that the S-shaped
transformation obtains soft edge maps similar to the
fixed threshold and the new fitness functions improve
the edge detection accuracy.",
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notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
EPS and the IET.",
- }
Genetic Programming entries for
Wenlong Fu
Mark Johnston
Mengjie Zhang
Citations