Spatial Domain Edge Detection of Image in Rainy Weather
|Veena Dohare1 , M.P. Parsai2|
1 Dept. of Electronics and Telecommunication, Jabalpur Engineering College, Jabalpur, India.
2 Dept. of Electronics and Telecommunication, Jabalpur Engineering College, Jabalpur, India. .
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Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-7 , Page no. 32-38, Jul-2017
Online published on Jul 30, 2017
Copyright © Veena Dohare, M.P. Parsai . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Veena Dohare, M.P. Parsai, “Spatial Domain Edge Detection of Image in Rainy Weather”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.7, pp.32-38, 2017.
MLA Style Citation: Veena Dohare, M.P. Parsai "Spatial Domain Edge Detection of Image in Rainy Weather." International Journal of Computer Sciences and Engineering 5.7 (2017): 32-38.
APA Style Citation: Veena Dohare, M.P. Parsai, (2017). Spatial Domain Edge Detection of Image in Rainy Weather. International Journal of Computer Sciences and Engineering, 5(7), 32-38.
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|Edges are the set of curved line segments where brightness level of image changes sharply. It is one of the most important information of an image which can helps to detect object boundary, its relative position within target area and many other useful information. In edge detection process, edges are retrieved from an image by spotting high intensity variations of the pixels. Edge detection of an image minimizes the amount of processed data effectively and discards information that is less important, keeping the important structural properties of an image. This paper presents a different approach to apply Gradient and LoG operator to get more continuous edges than the conventional one using MATLAB. Their results are compared using peak signal to noise ratio (PSNR). Two images in rainy weather are taken by my camera for case study. It can be used in many applications such as in object tracking, in data compression, in image analysis and medical imaging.|
|Key-Words / Index Term :|
|Gradient and LoG; Peak signal-to-noise ratio; Intensity level; Edge detection|
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