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Conference Papers Year : 2012

Fast pseudo-semantic segmentation for joint region-based hierarchical and multiresolution representation

Abstract

In this paper, we present a new scalable segmentation algorithm called JHMS (Joint Hierarchical and Multiresolution Segmentation) that is characterized by region-based hierarchy and resolution scalability. Most of the proposed algorithms either apply a multiresolution segmentation or a hierarchical segmentation. The proposed approach combines both multiresolution and hierarchical segmentation processes. Indeed, the image is considered as a set of images at different levels of resolution, where at each level a hierarchical segmentation is performed. Multiresolution implies that a segmentation of a given level is reused in further segmentation processes operated at next levels so that to insure contour consistency between different resolutions. Each level of resolution provides a Region Adjacency Graph (RAG) that describes the neighborhood relationships between regions within a given level of the multiresolution representation. Region label consistency is preserved thanks to a dedicated projection algorithm based on inter-level relationships. Moreover, a preprocess based on a quadtree partitioning reduces the amount of input data thus leading to a lower overall complexity of the segmentation framework. Experiments show that we obtain effective results when compared to the state of the art together with a lower complexity.
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Dates and versions

hal-00657805 , version 1 (09-01-2012)

Identifiers

Cite

Rafik Sekkal, Clément Strauss, François Pasteau, Marie Babel, Olivier Déforges. Fast pseudo-semantic segmentation for joint region-based hierarchical and multiresolution representation. SPIE Electronic Imaging - Visual Communications and Image Processing, Jan 2012, San Francisco, United States. pp.83050J, ⟨10.1117/12.908829⟩. ⟨hal-00657805⟩
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