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An Edge Detection Method for Grayscale Images based on BP Feedforward Neural Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 67 - Number 2 |
| Year of Publication: 2013 |
| Authors: Jesal Vasavada, Shamik Tiwari |
10.5120/11368-6627
|
Jesal Vasavada, Shamik Tiwari . An Edge Detection Method for Grayscale Images based on BP Feedforward Neural Network. International Journal of Computer Applications. 67, 2 ( April 2013), 22-28. DOI=10.5120/11368-6627
Abstract
The edges provide important visual information since they correspond to major physical and geometrical variations in scene object. Edge detection is a terminology in image processing that refers to algorithms which aim at identifying edges in an image. In this paper a Feedforward Neural Network (FNN) based algorithm is proposed to detect edges in gray scale images. The backpropagation learning algorithm is used to minimize the error. Standard deviation and gradient values are used as training patterns. In the end the network is tested for a number of different kinds of grayscale images. The proposed scheme is compared with Prewitt, Roberts, Sobel, LoG and other neural network based method in which binary training patterns are used. Our method has performed significantly better as compared to other methods.
References
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