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Comparative Analysis of Noisy Image Edge Detection Techniques using Different Parameters


Ashis Kumar Kar , Utkal University, Bhubaneswar; Mrutyunjaya Panda, Utkal University, Bhubaneswar


Prewitt, Sobel, LOG, Canny, Roberts, Salt and Pepper Noise, Gaussian Noise, Speckle Noise, PSNR, MSE, MAE


The most important goal of image processing is to interpret the content of image efficiently and finds the meaningful and significant information from it. The image obtained after transmission is often corrupted with noise. A noise is introduced in the transmission medium due to a noisy channel, errors during the measurement process and during quantization of the data for digital storage. Before applying image processing tools to an image, noise removal from images is done at highest priority. There are various noises like Salt and Pepper, Gaussian noise etc. and various filtering techniques available for removing the noises from the images like Mean filter, Median filter and Gaussian filter etc. So before applying edge detection techniques on an image it must be a noise free image. Edges are the fundamental features of the image and can be formed from the outlines of the object. Edge detection is generally used in image analysis and processing. There are several types of algorithm to detect the edges. In this paper, the comprehensive analysis is done on the several edge detection techniques such as Prewitt, Sobel, Canny, Roberts and Laplacian of Gaussian applied on a filtered image by applying Salt and Pepper noise, Gaussian noise and Speckle noise. They are analyzed based on the evaluation parameters PSNR, MSE and MAE. It is experimentally observed that Canny edge detector is working well than others. This work is implemented on Matlab R2013a.

Other Details

Paper ID: IJSRDV7I70375
Published in: Volume : 7, Issue : 7
Publication Date: 01/10/2019
Page(s): 536-544

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