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A Topological Measure for Image Object Recognition

  • Conference paper
Graphics Recognition. Recent Advances and Perspectives (GREC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3088))

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Abstract

All the effective object recognition systems are based on a powerful shape descriptor. We propose a new method for extracting the topological feature of an object. By connecting all the pixels constituting the object under the constraint to define the shortest path (minimum spanning tree) we capture the shape topology. The tree length is in the first approximation the key of our object recognition system. This measure (with some adjustments) make it possible to detect the object target in several geometrical configurations (translation / rotation) and it seems to have many desirable properties such as discrimination power and robustness to noise, that is the conclusion of the preliminary tests on characters and symbols.

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© 2004 Springer-Verlag Berlin Heidelberg

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Franco, P., Ogier, JM., Loonis, P., Mullot, R. (2004). A Topological Measure for Image Object Recognition. In: Lladós, J., Kwon, YB. (eds) Graphics Recognition. Recent Advances and Perspectives. GREC 2003. Lecture Notes in Computer Science, vol 3088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25977-0_26

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  • DOI: https://doi.org/10.1007/978-3-540-25977-0_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22478-5

  • Online ISBN: 978-3-540-25977-0

  • eBook Packages: Springer Book Archive

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