Scale and Rotation-Robust Genetic Programming-Based Corner Detectors
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- @InProceedings{Seo:2010:EvoINTELLIGENCE,
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author = "Kisung Seo and Youngkyun Kim",
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title = "Scale and Rotation-Robust Genetic Programming-Based
Corner Detectors",
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booktitle = "EvoINTELLIGENCE",
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year = "2010",
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editor = "Cecilia {Di Chio} and Stefano Cagnoni and
Carlos Cotta and Marc Ebner and Aniko Ekart and
Anna I. Esparcia-Alcazar and Chi-Keong Goh and
Juan J. Merelo and Ferrante Neri and Mike Preuss and
Julian Togelius and Georgios N. Yannakakis",
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volume = "6024",
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series = "LNCS",
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pages = "381--391",
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address = "Istanbul",
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month = "7-9 " # apr,
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-12238-5",
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DOI = "doi:10.1007/978-3-642-12239-2_40",
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abstract = "This paper introduces GP- (Genetic Programming-) based
robust corner detectors for scaled and rotated images.
Previous Harris, SUSAN and FAST corner detectors are
highly efficient for well-defined corners, but
frequently mis-detect as corners the corner-like edges
which are often generated in rotated images. It is very
difficult to avoid incorrectly detecting as corners
many edges which have characteristics similar to
corners. In this paper, we have focused on this
challenging problem and proposed using Genetic
Programming to do automated generation of corner
detectors that work robustly on scaled and rotated
images. Various terminal sets are presented and tested
to capture the key properties of corners. Combining
intensity-related information, several mask sizes, and
amount of contiguity of neighboring pixels of similar
intensity, allows a well-devised terminal set to be
proposed. This method is then compared to three
existing corner detectors on test images and shows
superior results.",
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notes = "EvoINTELLIGENCE'2010 held in conjunction with
EuroGP'2010 EvoCOP2010 EvoBIO2010",
- }
Genetic Programming entries for
Kisung Seo
Youngkyun Kim
Citations