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Scene Image Segmentation based on Perceptual Organization Chang Cheng, Andreas Koschan, David L. Page, and Mongi. A. Abidi
 

Summary: Scene Image Segmentation based on Perceptual Organization
Chang Cheng, Andreas Koschan, David L. Page, and Mongi. A. Abidi
The University of Tennessee, IRIS Lab
ABSTRACT
We propose a novel scene image segmentation algorithm
based on Perceptual Organization. We develop a Perceptual
Organization model by quantitatively incorporating a list of
Gestalt laws. The Perceptual Organization model can
capture the non-accidental structural relations among the
constituent parts of an object. The experimental results
show that our proposed method outperformed two
competing image segmentation approaches and achieved
good segmentation quality on various natural scene
environments.
Index Terms-- Boundary Detection, Boundary Energy,
Image Segmentation, Perceptual Organization
1. INTRODUCTION
A primary goal of image segmentation is to partition an
image into regions of coherent properties so that each region
corresponds to an object or area of interest. A challenge for

  

Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee
Koschan, Andreas - Imaging, Robotics, and Intelligent Systems, University of Tennessee

 

Collections: Computer Technologies and Information Sciences; Engineering