This paper illustrates a new object-oriented segmentation algorithm based on the cellular neural network (CNN) paradigm. The approach, which exploits rigorous model of the image contours, presents two remarkable features: 1) it provides more accurate segmented objects than the ones obtained by other CNN-based techniques; 2) it makes use of CNN templates that take into account the hardware characteristics imposed by the CNNUM. Results carried out for benchmark video sequences highlight the capabilities of the proposed technique.

New object-oriented segmentation algorithm based on the CNN paradigm

GRASSI, Giuseppe;
2006-01-01

Abstract

This paper illustrates a new object-oriented segmentation algorithm based on the cellular neural network (CNN) paradigm. The approach, which exploits rigorous model of the image contours, presents two remarkable features: 1) it provides more accurate segmented objects than the ones obtained by other CNN-based techniques; 2) it makes use of CNN templates that take into account the hardware characteristics imposed by the CNNUM. Results carried out for benchmark video sequences highlight the capabilities of the proposed technique.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/104047
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