Title :
Multiscale edge detection using first order R-filter
Author :
Gökmen, Muhittin ; Li, Ching-Chung
Author_Institution :
Electr. & Electron. Eng. Fac., Istanbul Tech. Univ., Turkey
fDate :
30 Aug-3 Sep 1992
Abstract :
A multiscale edge detection scheme using a first-order regularization filter (R-filter) is presented. After considering relationships with some of the optimal edge operators, it is shown that the first derivative of the R-filter, which is derived from the 1-D string functional has good edge localization performance. By utilizing this property, the detection performance is improved by combining multiscale edges through a simple yet effective integration scheme. The performance of the algorithm on synthetic and real images is evaluated by using both quantitative and qualitative measures, and compared with that of Canny edge detector
Keywords :
edge detection; filtering and prediction theory; 1-D string functional; Canny edge detector; R-filter; edge localization performance; first-order regularization filter; multiscale edge detection; qualitative measures; quantitative measures; real images; synthetic images; Computational geometry; Computer vision; Data mining; Detectors; Feature extraction; Filters; Image edge detection; Image sampling; Lighting; Signal sampling;
Conference_Titel :
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2920-7
DOI :
10.1109/ICPR.1992.201986