Comparison of various edge detection techniques

Edge detection is used to extract the important features (e.g.-line, curves and corners) which can be used for very handy purposes (e.g.-face recognition, computer vision algorithms). But extraction of Edges from images is an onerous job without effecting the structural properties of image what so ever. Edges in an image signify the abrupt changes in intensity values. So it becomes even more strenuous to extract edges when there is a noise in an image. The reason behind is that the noise also signify the swift changes in the intensity values of an image. In this paper the various edge detection techniques to extract out the edges efficiently and the comparison between them is explained. The comparison is drawn on the parameters- MSE, RMS, and PSNR. The techniques constitute -Robert's, prewitt, sobel and canny edge detection. The output of images is shown using the software Matlab.