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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 (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

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Computer Vision and Robotics (Autonomous Systems)
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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Computer Vision and Robotics (Autonomous Systems)

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