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Object Segmentation by Edges Features of Graph Cuts

Authors:
Weiwei Du
Yuki Masumoto
Nobuyuki Nakamori

Keywords: object segmentation, edges features, graph cuts, Gaussian Mixture Models

Abstract:
This paper proposes a simple graph cuts algorithm based edges features to object segmentation problems. Graph cuts are used to find the global optimum of a cost function based on boundary and region of an image. Gaussian Mixture Models (GMMs) are built based on the seeds which are given by user to the object and background in an image. The contribution of this paper is to add edges features to GMMs. The proposal can segment an object region having noisy edges and colors similarity between the object and background. Experimental results illustrate the validity of the proposal.

Pages: 388 to 393

Copyright: Copyright (c) IARIA, 2012

Publication date: November 18, 2012

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-230-1

Location: Lisbon, Portugal

Dates: from November 18, 2012 to November 23, 2012