Research Article
Preprocessing Methods to Remove Impulse Noise in Avian Pox affected Hen Image using Image Processing
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 98 - Issue 20 |
| Published: July 2014 |
| Authors: C. Hemalatha, S. Muruganand, R. Maheswaran |
10.5120/17298-7728
|
C. Hemalatha, S. Muruganand, R. Maheswaran . Preprocessing Methods to Remove Impulse Noise in Avian Pox affected Hen Image using Image Processing. International Journal of Computer Applications. 98, 20 (July 2014), 18-21. DOI=10.5120/17298-7728
@article{ 10.5120/17298-7728,
author = { C. Hemalatha,S. Muruganand,R. Maheswaran },
title = { Preprocessing Methods to Remove Impulse Noise in Avian Pox affected Hen Image using Image Processing },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 98 },
number = { 20 },
pages = { 18-21 },
doi = { 10.5120/17298-7728 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A C. Hemalatha
%A S. Muruganand
%A R. Maheswaran
%T Preprocessing Methods to Remove Impulse Noise in Avian Pox affected Hen Image using Image Processing%T
%J International Journal of Computer Applications
%V 98
%N 20
%P 18-21
%R 10.5120/17298-7728
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The main objective of this paper is to discuss the preprocessing method involved in the identification of avian pox disease in poultry farm. Due to the acquisition of the hen images and lighting variations noise can affect the images. Preprocessing is the first and very important step in image processing, after preprocessing we can do analysis in that image for future work. In this paper, impulse noise are removed using active filters. Mean filter, median filter and wiener filters are used for removing the noise. The performance evolution tests are made using Mean Square Error and Peak Signal to Noise Ratio. Based on the evolution test among the three filters median filter removes the impulse noise than the other filters.
References
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