NDLI: A non-reference measure for objective edge map evaluation

Content Provider	IEEE Xplore Digital Library
Author	Nercessian, S. Panetta, K. Agaian, S.
Copyright Year	2009
Description	Author affiliation: Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA (Nercessian, S.; Panetta, K.) \|\| Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA (Agaian, S.)
Abstract	Edge detection has been used extensively as a preprocessing step for many computer vision tasks. Due to its importance in image processing and the highly subjective nature of human evaluation and visual comparison of edge detectors, it is desirable to formulate objective edge map evaluation measures. One would like to use such a measure to make comparisons of results using the same edge detector with different parameters as well as to make comparisons of results using different edge detectors. Reconstruction-based measures have the clear advantage that they effectively incorporate original image data. In this paper, a general model for reconstruction-based measures is established in order to alleviate the shortcomings of the reconstruction-based measures, followed by the formulation of a new non-reference measure for objective edge map evaluation. Experimental results illustrate the effectiveness of the new measure both as a means of selecting optimal edge detector parameters and as a means of determining the relative performance of edge detectors for a given image.
Starting Page	4563
Ending Page	4568
File Size	423961
Page Count	6
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346779
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Detectors Biomedical measurements USA Councils Electric variables measurement Image processing Image reconstruction Computer vision Object detection Image analysis performance measures Edge detection objective evaluation
Content Type	Text
Resource Type	Article

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