Genetic Programming For Edge Detection: A Global Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Fu:2011:GPFEDAGA,
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title = "Genetic Programming For Edge Detection: A Global
Approach",
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author = "Wenlong Fu and Mark Johnston and Mengjie Zhang",
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pages = "254--261",
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booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
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year = "2011",
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editor = "Alice E. Smith",
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month = "5-8 " # jun,
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address = "New Orleans, USA",
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CEC.2011.5949626",
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abstract = "Edge detection is an important task in computer
vision. This paper describes a global approach to edge
detection using genetic programming (GP). Unlike most
traditional edge detection methods which use local
window filters, this approach directly uses an entire
image as input and classifies pixels directly as edges
or non-edges without preprocessing or postprocessing.
Shifting operations and common standard operators are
used to form the function set. Precision, recall and
true negative rate are used to construct the fitness
functions. This approach is examined and compared with
the Laplacian and Sobel edge detectors on three sets of
images providing edge detection problems of varying
difficulty. The results suggest that the detectors
evolved by GP outperform the Laplacian detector and
compete with the Sobel detector in most cases.",
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notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Wenlong Fu
Mark Johnston
Mengjie Zhang
Citations