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Summary: IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 3, MARCH 2012 1007
Outdoor Scene Image Segmentation Based on
Background Recognition and Perceptual Organization
Chang Cheng, Andreas Koschan, Member, IEEE, Chung-Hao Chen, David L. Page, and Mongi A. Abidi
Abstract--In this paper, we propose a novel outdoor scene image
segmentation algorithm based on background recognition and
perceptual organization. We recognize the background objects
such as the sky, the ground, and vegetation based on the color
and texture information. For the structurally challenging objects,
which usually consist of multiple constituent parts, we developed
a perceptual organization model that can capture the nonacci-
dental structural relationships among the constituent parts of the
structured objects and, hence, group them together accordingly
without depending on a priori knowledge of the specific objects.
Our experimental results show that our proposed method outper-
formed two state-of-the-art image segmentation approaches on
two challenging outdoor databases (Gould data set and Berkeley
segmentation data set) and achieved accurate segmentation
quality on various outdoor natural scene environments.
Index Terms--Boundary energy, image segmentation, percep-
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