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Journal of Electronic Imaging • Open Access

Survey of contemporary trends in color image segmentation
Author(s): Sreenath Rao Vantaram; Eli Saber

Paper Abstract

In recent years, the acquisition of image and video information for processing, analysis, understanding, and exploitation of the underlying content in various applications, ranging from remote sensing to biomedical imaging, has grown at an unprecedented rate. Analysis by human observers is quite laborious, tiresome, and time consuming, if not infeasible, given the large and continuously rising volume of data. Hence the need for systems capable of automatically and effectively analyzing the aforementioned imagery for a variety of uses that span the spectrum from homeland security to elderly care. In order to achieve the above, tools such as image segmentation provide the appropriate foundation for expediting and improving the effectiveness of subsequent high-level tasks by providing a condensed and pertinent representation of image information. We provide a comprehensive survey of color image segmentation strategies adopted over the last decade, though notable contributions in the gray scale domain will also be discussed. Our taxonomy of segmentation techniques is sampled from a wide spectrum of spatially blind (or feature-based) approaches such as clustering and histogram thresholding as well as spatially guided (or spatial domain-based) methods such as region growing/splitting/merging, energy-driven parametric/geometric active contours, supervised/unsupervised graph cuts, and watersheds, to name a few. In addition, qualitative and quantitative results of prominent algorithms on several images from the Berkeley segmentation dataset are shown in order to furnish a fair indication of the current quality of the state of the art. Finally, we provide a brief discussion on our current perspective of the field as well as its associated future trends.

Paper Details

Date Published: 4 October 2012
PDF: 28 pages
J. Electron. Imag. 21(4) 040901 doi: 10.1117/1.JEI.21.4.040901
Published in: Journal of Electronic Imaging Volume 21, Issue 4
Show Author Affiliations
Sreenath Rao Vantaram, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)

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