Conference Proceedings

Hierarchical Mutual Nearest Neighbour Image Segmentation

SM Abdullah, Peter Tischer, Sudanthi Wijewickrema, Andrew Paplinski, AWC Liew (ed.), B Lovell (ed.), C Fookes (ed.), J Zhou (ed.), Y Gao (ed.), M Blumenstein (ed.), Z Wang (ed.)

2016 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA) | IEEE | Published : 2016

Abstract

This paper presents a hierarchical image segmentation algorithm based on the principle of mutual nearest neighbours. Image segmentation remains a great challenge in the computer vision community. To solve this problem, various algorithms have been proposed in the literature. However, most of these algorithms depend heavily on thresholds or parameter settings. Furthermore, the majority of them do not recognise the hierarchical nature of the problem. In particular, there might not be a single best segmentation for an image as the level of detail that should be present in a segmentation will depend on the purpose for which that segmentation will be used. Many algorithms might provide good resul..

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