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Proceedings Paper

An image-set for identifying multiple regions/levels of interest in digital images
Author(s): Mustafa Jaber; Mark Bailly; Yuqiong Wang; Eli Saber
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Paper Abstract

In the field of identifying regions-of-interest (ROI) in digital images, several image-sets are referenced in the literature; the open-source ones typically present a single main object (usually located at or near the image center as a pop-out). In this paper, we present a comprehensive image-set (with its ground-truth) which will be made publically available. The database consists of images that demonstrate multiple-regions-of-interest (MROI) or multiple-levels-of-interest (MLOI). The former terminology signifies that the scene has a group of subjects/objects (not necessarily spatially-connected regions) that share the same level of perceptual priority to the human observer while the latter indicates that the scene is complex enough to have primary, secondary, and background objects. The methodology for developing the proposed image-set is described. A psychophysical experiment to identify MROI and MLOI was conducted, the results of which are also presented. The image-set has been developed to be used in training and evaluation of ROI detection algorithms. Applications include image compression, thumbnailing, summarization, and mobile phone imagery. fluor

Paper Details

Date Published: 24 September 2011
PDF: 7 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 813510 (24 September 2011); doi: 10.1117/12.893967
Show Author Affiliations
Mustafa Jaber, Rochester Institute of Technology (United States)
Mark Bailly, Rochester Institute of Technology (United States)
Yuqiong Wang, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)

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