DocumentCode
2579632
Title
A non-reference measure for objective edge map evaluation
Author
Nercessian, Shahan ; Panetta, Karen ; Agaian, Sos
Author_Institution
Dept. of Electr. & Comput. Eng., Tufts Univ., Medford, MA, USA
fYear
2009
fDate
11-14 Oct. 2009
Firstpage
4563
Lastpage
4568
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.
Keywords
computer vision; edge detection; image reconstruction; computer vision; edge detection; image processing; nonreference measure; objective edge map evaluation; reconstruction-based measures; Biomedical measurements; Computer vision; Detectors; Electric variables measurement; Image analysis; Image edge detection; Image processing; Image reconstruction; Object detection; USA Councils; Edge detection; objective evaluation; performance measures;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1062-922X
Print_ISBN
978-1-4244-2793-2
Electronic_ISBN
1062-922X
Type
conf
DOI
10.1109/ICSMC.2009.5346779
Filename
5346779
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