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Analyzing Roberts Edge Detector for Digital Images Corrupted with Noise

Author(s): Raman Maini, Himanshu Aggarwal

Journal: International Journal of Computer and Network Security
ISSN 2076-2739

Volume: 2;
Issue: 1;
Start page: 35;
Date: 2010;
Original page

Keywords: Digital Images | Noise | Mask | Edge Detection

Edge detection is difficult in noisy images, since both the noise and the edges contain high-frequency content. Attempts to reduce the noise result in blurred and distorted edges. Operators used on noisy images are typically larger in scope, so they can average enough data to discount localized noisy pixels. This results in less accurate localization of the detected edges. So, it is crucial to have a good understanding of edge detection algorithms. This paper evaluates the performance of Roberts Edge Detector for detection of edges in digital images corrupted with different kinds of noise. Different kinds of noise are studied in order to evaluate the performance of the Roberts Edge Detector. Further, the various standard test Images are examined to validate our results. The software is developed using MATLAB 7.5.0. It has been observed that the Roberts Edge Detector works effectively for the digital images corrupted with Poisson Noise where as its performances reduces sharply for other kinds of noise in digital images.
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