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Optical Engineering

Knowledge-based control in multisensor image processing and recognition
Author(s): Fabio Roli; Franco Fontana; Paolo Pellegretti; Carlo Dambra
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Paper Abstract

An approach to the control of multisensor image processing and recognition based on a suitable representation of control knowledge in symbolic form is presented. A hierarchical organization of control knowledge, corresponding to a decomposition of the image recognition process into subprocesses, is proposed. The knowledge for the control of the low-level and high-level phases is described in detail. The control problem involved in the automatic selection and tuning of image processing algorithms is addressed using data structures representing advised sequences of algorithms, a symbolic representation of quality control, and control strategies with backtracking capabilities. Error handling in the high-level phase is faced by a functional decomposition of the error-handling task into error states and types and by a hierarchical representation of the control knowledge for error detection and recovery. Results obtained in a real-world multisensor application are reported, and the improvement in classification accuracy obtained by the proposed error-handling mechanisms is evaluated.

Paper Details

Date Published: 1 June 1993
PDF: 14 pages
Opt. Eng. 32(6) doi: 10.1117/12.134176
Published in: Optical Engineering Volume 32, Issue 6
Show Author Affiliations
Fabio Roli, Univ. of Genoa (Italy)
Franco Fontana, Univ. of Genoa (Italy)
Paolo Pellegretti, Univ. of Genoa (Italy)
Carlo Dambra, Univ. di Genova (Italy)

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