DocumentCode
288884
Title
Contribution of Canny-Deriche filter and artificial neural networks to image segmentation
Author
Koffi, R. ; Solaiman, B. ; Mouchot, M.C.
Author_Institution
Ecole Nat. Superieure des Telecommun. de Bretagne, Brest, France
Volume
6
fYear
1994
fDate
27 Jun- 2 Jul 1994
Firstpage
4044
Abstract
In this paper, an image segmentation method based on an edge detection view is presented. This method uses the contribution of two approaches: the optimal edge detector proposed by J. Canny, and then extended to the optimal recursive filter by R. Deriche; and the artificial neural network approach. Combining these two methods, the hysteresis stage needed in the technique developed by Deriche is avoided without damaging the segmentation result. Therefore, thresholds required in hysteresis phase and, which are usually quite difficult to find are no more needed. Experimental results show the validity of this method
Keywords
edge detection; image segmentation; neural nets; recursive filters; Canny-Deriche filter; artificial neural networks; edge detection; image segmentation; optimal edge detector; optimal recursive filter; Artificial neural networks; Detectors; Filtering; Finite impulse response filter; Humans; Hysteresis; IIR filters; Image edge detection; Image segmentation; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374861
Filename
374861
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