Derivative structures: a step toward knowledge and vision engines

Igor Kuvychko

doi:10.1117/12.360322

26 August 1999 Derivative structures: a step toward knowledge and vision engines

Igor Kuvychko

Proceedings Volume 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision; (1999) https://doi.org/10.1117/12.360322
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

This paper shows how graph and diagrammatic structures could evolve into the more abstract ones that carry knowledge about the original in the form of relations and hierarchies. They can play a role of context, or 'measurement device', giving the ability to analyze. Such derivative structures can drive processes in distributed networks, like firing a spatio-temporal pattern, creating another structure, etc., therefore, performing top-bottom algorithms. In the mid-80 PDP group came closely to the problem of knowledge representation by distributed graphs called 'schemata'. Their models were based on the neural networks. I argue that the actual level of problems that neural network can solve is lower than required for knowledge representation. The 'hardware unit' of intelligence could rather be a 'neural assembly' that combines both discrete and continuous features, and is able to perform both diagrammatic and graphs operations, being the basis of intelligence. The representation of such 'neural assembly' as a fuzzy logic unit with active kernel and less active fuzzy boundaries is proposed. Such units can make logical operations spatially and temporarily, acting on a diagrammatic manner. Connections between the set of such activated units make spatio-temporal pattern really looking like a set of nodes connected via links on more abstract level. The article shows that image understanding is the are where derivative structures play important role, making images and scene self-describing without any work description, and truly invariant to any transformations. That opens the way to the new technologies in computer vision and image databases.

Citation Download Citation

Igor Kuvychko "Derivative structures: a step toward knowledge and vision engines", Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); https://doi.org/10.1117/12.360322

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