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The Boolean Map Distance: Theory and Efficient Computation
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2017 (English)In: International Conference on Discrete Geometry for Computer Imagery / [ed] Walter G. Kropatsch, Nicole M. Artner, Ines Janusch, Springer, 2017, Vol. 10502Conference paper, Published paper (Refereed)
Abstract [en]

We propose a novel distance function, the boolean map distance (BMD), that defines the distance between two elements in an image based on the probability that they belong to different components after thresholding the image by a randomly selected threshold value. This concept has been explored in a number of recent publications, and has been proposed as an approximation of another distance function, the minimum barrier distance (MBD). The purpose of this paper is to introduce the BMD as a useful distance function in its own right. As such it shares many of the favorable properties of the MBD, while offering some additional advantages such as more efficient distance transform computation and straightforward extension to multi-channel images.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 10502
Series
Lecture notes in computer science
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Science
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-333809DOI: 10.1007/978-3-319-66272-5_27OAI: oai:DiVA.org:uu-333809DiVA: diva2:1157967
Conference
International Conference on Discrete Geometry for Computer Imagery
Available from: 2017-11-17 Created: 2017-11-17 Last updated: 2017-11-17

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Centre for Image AnalysisComputerized Image Analysis and Human-Computer InteractionDivision of Visual Information and Interaction
Computer Vision and Robotics (Autonomous Systems)Computer Science

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