Record link: 
http://hdl.handle.net/20.500.12708/54569
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Title: 
Automated Petroglyph Image Segmentation with Interactive Classifier Fusion
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Citation: 
Seidl, M., & Breiteneder, C. (2012). Automated Petroglyph Image Segmentation with Interactive Classifier Fusion. In Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing - ICVGIP ’12. Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), Chennai, India, Non-EU. https://doi.org/10.1145/2425333.2425399
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Publisher DOI: 
10.1145/2425333.2425399
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Seidl, Markus 
Breiteneder, Christian 
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Organisational Unit: 
E193-06 - Forschungsbereich Interactive Media Systems 
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Published in: 
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing - ICVGIP '12 
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Date (published): 
2012
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Event name: 
Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) 
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Event date: 
12-Dec-2010 - 15-Dec-2010
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Event place: 
Chennai, India, Non-EU
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Number of Pages: 
8
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Keywords: 
Image segmentation; experimental sutdy; pixel classification; image features; pattern recognition; rock art; petroglyphs
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Abstract: 
The number of high quality images of rock panels containing petroglyphs grows steadily. Different time-consuming manual methods to determine and document the exact shapes and spatial locations of petrogyphs on a panel have been carried out over decades. The first step for classification and retrieval of petroglyphs is the segmentation of the images. In this paper, we present and evaluate an automated approach to segment petroglyph images.
de
 
The number of high quality images of rock panels containing petroglyphs grows steadily. Different time-consuming manual methods to determine and document the exact shapes and spatial locations of petrogyphs on a panel have been carried out over decades. The first step for classification and retrieval of petroglyphs is the segmentation of the images. In this paper, we present and evaluate an automated approach to segment petroglyph images.
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Science Branch: 
Mathematik, Informatik
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Appears in Collections:
Conference Paper

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