CBR for the reuse of Image Processing knowledge : a recursive retrieval/adaptation strategy

Valérie Ficet-Cauchard 1 Christine Porquet 1 Marinette Revenu 1
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
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.
Type de document :
Communication dans un congrès
ICCBR'99, 1999, München, Germany. pp.438-452, 1999, 〈10.1007/3-540-48508-2_32〉
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Valérie Ficet-Cauchard, Christine Porquet, Marinette Revenu. CBR for the reuse of Image Processing knowledge : a recursive retrieval/adaptation strategy. ICCBR'99, 1999, München, Germany. pp.438-452, 1999, 〈10.1007/3-540-48508-2_32〉. 〈hal-00869604〉



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