Abstract
. The development of an Image Processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. Our major objective is to help IP experts reuse parts of their applications. A first work towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of our interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, we explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system’s implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application.
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References
A. Bonzano, P. Cunningham & B. Smyth Using introspective learning to improve retrieval in CBR: A case study in air traffic control, ICCBR’97, Rhode Island, USA, July 1997.
P. Caulier & B. Houriez A Case-Based Reasoning Assistance System in Telecommunications Networks Management, XPS’95, Kaiserslautern, Germany, 1995.
R. Clouard, A. Elmoataz, C. Porquet, M. Revenu, Borg:A knowledge-based system for automatic generation of image processing programs, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 21, n.2, pp. 128–144, February, 1999.
A. Elmoataz, Mécanismes opératoires d’un segmenteur d’images non dédié: définition d’une base d’opérateurs et6 implementation, Thèse de Doctorat, Caen, July 1990.
V. Ficet-Cauchard, C. Porquet & M. Revenu, An Interactive Case-Based Reasoning System for the Development of Image Processing Applications, EWCBR’98, Dublin, Ireland, pp. 437–447, September 1998.
V. Ficet-Cauchard, Réalisation d’un système d’aide à la conception d’applications de Traitement d’Images: une approche basée sur le Raisonnement à Partir de Cas, Thèse de Doctorat, Caen, January 1999.
H. Munoz-Avila, D. Aha, L. Breslow & D. Nau HICAP: An Interactive Case-Based Planning Architecture and its Application to Noncombatant Evacuation Operations. IAAI-99.
B.D. Netten & R.A. Vingerhoeds Structural Adaptation by Case Combination in EADOCS, GWCBR’96, Bad Honnef, Germany, March 1997.
B. Prasad, Planning With Case-Based Structures, AAAI Fall Symposium, MIT Campus, Cambridge, Massachusetts, November 1995.
Russ, John C. (1995) The Image Processing Handbook, second edition, CRC Press, 1995.
B. Smyth, Case-Based Design, Doctoral Thesis of the Trinity College, Dublin, Ireland, April 1996.
M. Veloso, H. Munoz-Avila & R. Bergmann Cased-based planning: selected methods and systems, AI Communications, vol. 9, n. 3, September 1996.
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Ficet-Cauchard, V., Porquet, C., Revenu, M. (1999). CBR for the Reuse of Image Processing Knowledge: a Recursive Retrieval/Adaptation Strategy. In: Althoff, KD., Bergmann, R., Branting, L. (eds) Case-Based Reasoning Research and Development. ICCBR 1999. Lecture Notes in Computer Science, vol 1650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48508-2_32
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DOI: https://doi.org/10.1007/3-540-48508-2_32
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