DocumentCode :
3110322
Title :
Image reconstruction for quality assessment of edge detectors
Author :
Govindarajan, Barghavi ; Panetta, Karen A. ; Agaian, Sos
Author_Institution :
Dept. of Electr. Eng., Tufts Univ., Medford, MA
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
691
Lastpage :
696
Abstract :
Extraction of the edges is a key step in image processing and there is still a continuing research effort to develop new and effective edge detection algorithms. Despite this fact, there is no single, reliable and efficient metric to evaluate the quality of an edge detector. We introduce an original method for image reconstruction that leads to edge evaluation based on image estimation. A new quantitative metric for assessment of the performance of the edge detector is also presented. The operation of the measure is established on a diverse image database using standard edge detection algorithms and the one based on partial derivatives of Boolean functions. The uses of the measure for an assortment of purposes are demonstrated and these are backed by visual assessment as well as some distance-based error functions applied on synthetic images.
Keywords :
Boolean functions; edge detection; image reconstruction; Boolean functions; distance based error functions; diverse image database; edge detection algorithm; edge detector; edge evaluation; image estimation; image processing; image reconstruction; quality assessment; quantitative metric; visual assessment; Boolean functions; Detectors; Image databases; Image edge detection; Image processing; Image reconstruction; Interpolation; Measurement standards; Quality assessment; Signal processing algorithms; Edge evaluation; detector parameters; image reconstruction; interpolation; quality measure; structural similarity; weighted median;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on
Conference_Location :
Singapore
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2383-5
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2008.4811358
Filename :
4811358
Link To Document :
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