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Performance Evaluation of Improved Skew Detection and Correction using FFT and Median Filtering

by Neha Watts, Jyoti Rani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 15
Year of Publication: 2014
Authors: Neha Watts, Jyoti Rani
10.5120/17599-8174

Neha Watts, Jyoti Rani . Performance Evaluation of Improved Skew Detection and Correction using FFT and Median Filtering. International Journal of Computer Applications. 100, 15 ( August 2014), 7-16. DOI=10.5120/17599-8174

@article{ 10.5120/17599-8174,
author = { Neha Watts, Jyoti Rani },
title = { Performance Evaluation of Improved Skew Detection and Correction using FFT and Median Filtering },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 15 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 7-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number15/17599-8174/ },
doi = { 10.5120/17599-8174 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:30:01.622372+05:30
%A Neha Watts
%A Jyoti Rani
%T Performance Evaluation of Improved Skew Detection and Correction using FFT and Median Filtering
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 15
%P 7-16
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a new skew detection and correction technique using FFT & median filtering. It is found that there are many techniques based on skew correction which have been proposed so far by different researchers. It has been found that the most of existing techniques introduce artifacts while doing the skew correction. So to overcome this problem an integrated approach is presented in this research work. The proposed algorithm is planned and implemented in MATLAB using Image processing toolbox. To illustrate the algorithm 25 skewed images are taken for experimental purpose. The proposed algorithm has shown quite active results than previous techniques . The accuracy of the proposed algorithm is 99%.

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Index Terms

Computer Science
Information Sciences

Keywords

Optical character recognition (OCR) systems Document analysis systems (DAS) BER.

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