Lampert, Thomas and O'Keefe, Simon orcid.org/0000-0001-5957-2474 (2008) Active Contour Detection of Linear Patterns in Spectrogram Images. In: 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6. 19th International Conference on Pattern Recognition (ICPR 2008), 08-11 Dec 2008 IEEE , Tampa , pp. 3350-3353.
Abstract
This paper proposes an extension to the active contour algorithm for the detection of linear patterns within remote sensing and vibration data. The proposed technique uses an alternative energy force, overcoming the limitations of the original algorithm, which relies upon simple energy formulations to extract intensity and gradient information from an image. We overcome these by forming a noise model, which is used to detect a feature's presence, and by integrating information from several locations within an image to strengthen the detection process.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Keywords: | edge detection,feature extraction, geophysical signal processing, remote sensing ,contour detection ,energy force ,feature detection ,image gradient information, image intensity extraction ,linear pattern ,remote sensing ,spectrogram |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 07 Jun 2012 18:10 |
Last Modified: | 17 Dec 2024 00:32 |
Published Version: | https://doi.org/10.1109/ICPR.2008.4761214 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICPR.2008.4761214 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:67978 |