CFP last date
22 April 2024
Reseach Article

Extraction of Random Data from .png/.tif/.jpeg Image using Prewitt Operator

by Tushar Nayyar, Sarvpreet Singh, Karamdeep Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 160 - Number 2
Year of Publication: 2017
Authors: Tushar Nayyar, Sarvpreet Singh, Karamdeep Singh
10.5120/ijca2017912966

Tushar Nayyar, Sarvpreet Singh, Karamdeep Singh . Extraction of Random Data from .png/.tif/.jpeg Image using Prewitt Operator. International Journal of Computer Applications. 160, 2 ( Feb 2017), 7-12. DOI=10.5120/ijca2017912966

@article{ 10.5120/ijca2017912966,
author = { Tushar Nayyar, Sarvpreet Singh, Karamdeep Singh },
title = { Extraction of Random Data from .png/.tif/.jpeg Image using Prewitt Operator },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 160 },
number = { 2 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume160/number2/27043-2017912966/ },
doi = { 10.5120/ijca2017912966 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:20.045028+05:30
%A Tushar Nayyar
%A Sarvpreet Singh
%A Karamdeep Singh
%T Extraction of Random Data from .png/.tif/.jpeg Image using Prewitt Operator
%J International Journal of Computer Applications
%@ 0975-8887
%V 160
%N 2
%P 7-12
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this article, a method has been proposed which can be utilized for the extraction of random required data from .jpeg/.png/.tif images. Firstly, the concepts of edge detection in image processing and how it can be used for various applications are being introduced. Then, various steps that are involved in the process of edge detection are discussed in the paper. An algorithm has been developed for the extraction of required data from .jpeg/.png/.tif images. MATLAB® has been used to carry out numerical simulations. It has been found in the study that for the efficient extraction of data from .jpeg/.png/.gif/.tif images, the font size should be > 36 and the considered image should be a high contrast with threshold 0.1 to 0.34.

References
  1. Giri, P. S. (2003) Text information extraction and analysis from images using digital image processing techniques. International Journal on Advanced Computer Theory and Engineering (IJACTE), 2 (2013).
  2. Sawant S., Baji, S. (2016) Handwritten character and word recognition using their geometrical features through neural networks. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 5 (2016).
  3. Singla, G., Kumar, P. (2013). Extract the punjabi word with edge detector from machine printed document images. International Journal of Computer Science & Engineering Technology (IJCSET), 4 (2013).
  4. Tanuja k, usha kumara v, suhma TM (2015). Handwritten hindi character recognition system using edge detection & neural network. International Journal of Advanced Technology and Engineering Exploration, 2 (2015).
  5. Deborah, M., Pratap, C. S. (2014). Detection of fake currency using Image Processing. (?), 1 (2014).
  6. https://www.tutorialspoint.com/dip/concept_of_edge_detection.html
  7. http://www.cse.usf.edu/~r1k/MachineVisionBook/MachineVision.files/MachineVision_Chapter5.pdf
  8. Digital image processing 3rd edition by Rafael c Gonzales and Richard e woods.
  9. https://web.cs.wpi.edu/~emmanuel/courses/cs545/S14/slides/lecture05.pdf
  10. http://www.xinapse.com/Manual/masking.html
  11. https://www.cse.unr.edu/~bebis/CS791E/Notes/EdgeDetection.pdf
Index Terms

Computer Science
Information Sciences

Keywords

Pixels MATLAB® Masking Prewitt Sobel