Complementary Approach for Image Edge Detection Using Rough Mirror Mapping in Neural Network

Abstract

In this paper, a complementary approach has applied to obtain the available edges in the image. The complementary image has obtained by subtracting the rough mirror mapped image from the input image. The universal approximation capability of feedforward neural network has applied to define the rough mirror mapping. Multilayer perceptron network and radial basis function network have considered obtaining the mapping. Effect of better learning has also explored in both network by applying adaptivenesss in their transform function available in the active nodes. Single image based training has given for few number of iterations in the development of mapping process.  It is observed that proposed method has self adjusted content aware oriented edge detection where as many existing methods like Sobel, Prewitt have shown their limitations in observing the edges associated with contents having similar shade in the surroundings.