SPECIAL ISSUE: New Trends in Artificial Vision and Artificial Intelligence; Edited by M. De Gregorio and M. FrucciNo Access

CASE-BASED-REASONING FOR IMAGE SEGMENTATION

MARIA FRUCCI

Institute of Cybernetics "E.Caianiello", CNR, Pozzuoli (Naples), Italy

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PETRA PERNER

Institute of Computer Vision and Applied Computer Science, Leipzig, Germany

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, and

GABRIELLA SANNITI DI BAJA

Institute of Cybernetics "E.Caianiello", CNR, Pozzuoli (Naples), Italy

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https://doi.org/10.1142/S0218001408006491Cited by:13 (Source: Crossref)

Abstract

This paper proposes to use case-based-reasoning for grey-level image segmentation. Different approaches to image segmentation have been proposed in the literature. The selection of the segmentation approach and the assignment of the values to the parameters involved in the selected algorithm depend on image domain and on the specific application. Case-based-reasoning seems a promising way to make the above selection automatic. In this paper, we describe the results of a preliminary study done in this respect. In particular, we refer to the automatic selection of the values of the parameters for a new watershed image segmentation algorithm.

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CASE-BASED-REASONING FOR IMAGE SEGMENTATION

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