DocumentCode :
629894
Title :
A novel neural network approach for image edge detection
Author :
Abid, Sabeur ; Fnaiech, Farhat ; Ben Braiek, Ezzedine
Author_Institution :
Res. team: Signal, Image & Intell. Control of Ind. Syst., Ecole Super. des Sci. et Tech. de Tunis (ESSTT), Tunis, Tunisia
fYear :
2013
fDate :
21-23 March 2013
Firstpage :
1
Lastpage :
6
Abstract :
In this work a new method for image edge detection based on multilayer perceptron (MLP) is proposed. The method is based on updating a MLP to learn a set of contours drawn on a 3×3 grid and then take advantage of the network generalization capacity to detect different edge details even for very noisy images. The method is applied first to Gray scale images and can be easily extended to color ones. Simulations on synthetic and real image show much promised results in term of precision and localization. Moreover the method works well even for very low contrast images for which other edge operators fail.
Keywords :
edge detection; image colour analysis; multilayer perceptrons; MLP; gray scale image; image edge detection; low contrast image; multilayer perceptron; network generalization capacity; neural network; Biological neural networks; Databases; Detectors; Image edge detection; Noise measurement; Shape; classical edge detection operators; edge detection; multilayer perceptron (MLP);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering and Software Applications (ICEESA), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-6302-0
Type :
conf
DOI :
10.1109/ICEESA.2013.6578360
Filename :
6578360
Link To Document :
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