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Cognitive Vision and Perceptual Grouping by Production Systems with Blackboard Control – An Example for High-Resolution SAR-Images

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 4))

Abstract

The laws of gestalt-perception play an important role in human vision. Psychological studies identified similarity, good continuation, proximity and symmetry as important inter-object relations that distinguish perceptive gestalts from arbitrary sets of clutter objects. Particularly, symmetry and continuation possess a high potential in detection, identification, and reconstruction of man-made objects. This contribution focuses on coding this principle in an automatic production system. Such systems capture declarative knowledge. Procedural details are defined as control strategy for an interpreter. Often an exact solution is not feasible while approximately correct interpretations of the data with the production system are sufficient. Given input data and a production system the control acts accumulatively instead of reducing. The approach is assessment driven features any-time capability and fits well into the recently discussed paradigms of cognitive vision. An example from automatic extraction of groupings and symmetry in man-made structure from high resolution SAR-image data is given. The contribution also discusses the relations of such approach to the “mid-level” of what is today proposed as “cognitive vision”.

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Michaelsen, E., Middelmann, W., Sörgel, U. (2007). Cognitive Vision and Perceptual Grouping by Production Systems with Blackboard Control – An Example for High-Resolution SAR-Images. In: Braz, J., Ranchordas, A., Araújo, H., Jorge, J. (eds) Advances in Computer Graphics and Computer Vision. Communications in Computer and Information Science, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75274-5_20

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  • DOI: https://doi.org/10.1007/978-3-540-75274-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75272-1

  • Online ISBN: 978-3-540-75274-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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