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Genetic programming for edge detection based on figure of merit

Authors:

Wenlong Fu,

Mark Johnston,

Mengjie ZhangAuthors Info & Claims

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

Pages 1483 - 1484

https://doi.org/10.1145/2330784.2331003

Published: 07 July 2012 Publication History

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Abstract

The figure of merit (FOM) is popular for testing an edge detector's performance, but there are very few reports using FOM as an evaluation method in the learning stage of supervised learning methods. In this study, FOM is investigated as a fitness function in Genetic Programming (GP) for edge detection. Since FOM has some drawbacks from type II errors, new fitness functions are developed based on FOM in order to address these weaknesses. Experimental results show that FOM can be used to evolve GP edge detectors that perform better than the Sobel detector, and the new fitness functions clearly improve the ability of GP edge detectors to find edge points and give a single response on edges, compared with the fitness function using FOM.

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Fu WJohnston MZhang M(2016)Genetic programming for edge detectionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-014-1585-120:3(1231-1248)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1007/s00500-014-1585-1
Fu WJohnston MZhang M(2013)Automatic construction of gaussian-based edge detectors using genetic programmingProceedings of the 16th European conference on Applications of Evolutionary Computation10.1007/978-3-642-37192-9_37(365-375)Online publication date: 3-Apr-2013
https://dl.acm.org/doi/10.1007/978-3-642-37192-9_37

Index Terms

Genetic programming for edge detection based on figure of merit
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Interest point and salient region detections

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Published In

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

July 2012

1586 pages

ISBN:9781450311786

DOI:10.1145/2330784

Editor:
Terence Soule
University of Idaho, USA
,
General Chair:
Jason H. Moore
Dartmouth College, USA

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Association for Computing Machinery

New York, NY, United States

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Published: 07 July 2012

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GECCO '12: Genetic and Evolutionary Computation Conference

July 7 - 11, 2012

Pennsylvania, Philadelphia, USA

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Fu WJohnston MZhang M(2016)Genetic programming for edge detectionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-014-1585-120:3(1231-1248)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1007/s00500-014-1585-1
Fu WJohnston MZhang M(2013)Automatic construction of gaussian-based edge detectors using genetic programmingProceedings of the 16th European conference on Applications of Evolutionary Computation10.1007/978-3-642-37192-9_37(365-375)Online publication date: 3-Apr-2013
https://dl.acm.org/doi/10.1007/978-3-642-37192-9_37

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Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection

Automatic construction of gaussian-based edge detectors using genetic programming

Genetic programming for edge detection: a Gaussian-based approach

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Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection

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Genetic programming for edge detection: a Gaussian-based approach

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