Adding color sensitivity to the shape adaptive image ray transform
Adding color sensitivity to the shape adaptive image ray transform
The Image Ray Transform (IRT) is a recent approach to extract structures at a low level by mimicking the attributes of light rays. We suggest an extension of IRT to detect shapes of chosen colors. The new approach uses the CIEL*a*b* color model within the IRT’s light ray analogy. The capability of the extended IRT using color information is evaluated for correct shape location by conventional methods such as the Hough Transform. We show that the new approach can indeed be used to detect shapes of specified colors. Further work will aim to be expanded descriptive capability of new extraction.
978-3-319-14363-7
779-788
Oh, Ah Reum
a6c43beb-1d6e-411f-806f-7bb48501040b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
December 2014
Oh, Ah Reum
a6c43beb-1d6e-411f-806f-7bb48501040b
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Oh, Ah Reum and Nixon, Mark S.
(2014)
Adding color sensitivity to the shape adaptive image ray transform.
10th International Symposium on Visual Computing (ISVC 2014), Las Vegas, United States.
08 - 10 Dec 2014.
.
(doi:10.1007/978-3-319-14364-4_75).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The Image Ray Transform (IRT) is a recent approach to extract structures at a low level by mimicking the attributes of light rays. We suggest an extension of IRT to detect shapes of chosen colors. The new approach uses the CIEL*a*b* color model within the IRT’s light ray analogy. The capability of the extended IRT using color information is evaluated for correct shape location by conventional methods such as the Hough Transform. We show that the new approach can indeed be used to detect shapes of specified colors. Further work will aim to be expanded descriptive capability of new extraction.
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Published date: December 2014
Venue - Dates:
10th International Symposium on Visual Computing (ISVC 2014), Las Vegas, United States, 2014-12-08 - 2014-12-10
Organisations:
Vision, Learning and Control
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Local EPrints ID: 374232
URI: http://eprints.soton.ac.uk/id/eprint/374232
ISBN: 978-3-319-14363-7
PURE UUID: 910ed9b8-1afa-4eac-8e3f-686f0ce03b98
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Date deposited: 11 Feb 2015 11:32
Last modified: 15 Mar 2024 02:35
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Author:
Ah Reum Oh
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