1 June 1993 Knowledge-based control in multisensor image processing and recognition
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Optical Engineering, 32(6), (1993). doi:10.1117/12.134176
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.
Fabio Roli, Franco Fontana, Paolo Pellegretti, Carlo Dambra, "Knowledge-based control in multisensor image processing and recognition," Optical Engineering 32(6), (1 June 1993). http://dx.doi.org/10.1117/12.134176

Image processing

Image segmentation

Image filtering

Detection and tracking algorithms

Image quality

Image processing algorithms and systems

Magnetic resonance imaging

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