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A Comparison of Neuro-Fuzzy and Traditional Image Segmentation Methods for Automated Detection of Buildings in Aerial Photos
Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2002 (English)In: Proceedings of PCV'02: PHOTOGRAMMETRIC COMPUTER VISION 2002, 2002Conference paper, Published paper (Other scientific)
Abstract [en]

Using a set of colour-infrared aerial photos, we compare a newly developed neural net based clustering method with a method based on the classical ISODATA algorithm. The primary focus is on the detection of buildings and it shows that while the traditiona

Place, publisher, year, edition, pages
2002.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-42231OAI: oai:DiVA.org:uu-42231DiVA: diva2:70132
Available from: 2005-08-25 Created: 2005-08-25

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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