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An Efficient Method of Image Segmentation for Harvest Time Identification

by Monika Bhatnagar, Prashant Kumar Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 7
Year of Publication: 2014
Authors: Monika Bhatnagar, Prashant Kumar Singh
10.5120/15222-3734

Monika Bhatnagar, Prashant Kumar Singh . An Efficient Method of Image Segmentation for Harvest Time Identification. International Journal of Computer Applications. 87, 7 ( February 2014), 31-34. DOI=10.5120/15222-3734

@article{ 10.5120/15222-3734,
author = { Monika Bhatnagar, Prashant Kumar Singh },
title = { An Efficient Method of Image Segmentation for Harvest Time Identification },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 7 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number7/15222-3734/ },
doi = { 10.5120/15222-3734 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:19.746639+05:30
%A Monika Bhatnagar
%A Prashant Kumar Singh
%T An Efficient Method of Image Segmentation for Harvest Time Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 7
%P 31-34
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of development and advancements in every research and technology is to provide easy solutions to any user's problems including the day to day ones. One problem that a farmer might face is to identify whether his crop is ready for harvesting or not. Hence the efforts are taken to figure out an easy solution for a farmer where he can use his cellular phone to identify whether his crop is ready for harvesting or not. This he can do by taking picture of his crop through the digital camera of his cellular phone. Therefore image processing plays an active role to figure out the solution to this problem. This paper proposes image segmentation of the image of a crop such as tomato to identify whether the crop is ripe enough or not. The feature that is extracted for image segmentation is moment. The classification technique used for segmentation is K-means clustering algorithm. The values for the segmented image viz. Mismatching Rate, Misclassification Rate, PSNR and MSE are then calculated Then to identify how much the system is robust noise is inserted in the image and then again the image is segmented and the above mentioned values are calculated. Then the image is denoised and again segmentation of the image is performed and the same process is followed. This paper presents the above mentioned process and the system produces equivalent results in all the three cases. The research work presents here the result of the image segmentation done on the image of a tomato using MATLAB version 7. 10.

References
  1. Margaret H. Dunham," Data mining Introductory and Advanced Topics", pp 10-13, pp 119-159,7 Edition 2011, Pearson
  2. Hu Min, Yang Shuangyuan, "Overview of Image Mining Research", published in The 5th International Conference on Computer Science & Education Hefei, China. August 24–27, 2010, DOI 978-1-4244-6005-2/10/ ©2010 IEEE
  3. Ashish Phophalia, Suman K. Mitra, Charu Chawla," A Study on Image Segmentation Using Moments ", published in Asian Journal Of Computer Science And Information Technology,Volume 2,Issue 5(2012), ISSN 2249-5126,pp 89 – 93.
  4. Piotr Dollár, Zhuowen Tu, Hai Tao and Serge Belongie ,"Feature Mining for Image Classification", published in 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 18-23 June 2007, Minneapolis, Minnesota, USA.
  5. Hu Min, Yang Shuangyuan, "Overview of Image Mining Research", published in The 5th International Conference on Computer Science & Education Hefei, China. August 24–27, 2010, DOI 978-1-4244-6005-2/10/ ©2010 IEEE
  6. G. Polder, G. W. A. M. van der Heijden, I. T. Young, " Spectral Image Analysis for Measuring ripeness of Tomatoes", published in American Society of Agricultural Engineers (2002), Vol. 45(4): 1155-1161, ISSN 0001–2351
  7. Hassan Asadollahi, Morteza Sabery Kamarposhty, Mir Majid Teymoori ,"Classification and Evaluation of Tomato Images Using Several Classifier", published in 2009 International Association of Computer Science and Information Technology - Spring Conference, 978-0-7695-3653-8/09 © 2009 IEEE DOI 10. 1109/IACSIT-SC. 2009. 47
  8. Giuseppe Amato, Paolo Bolettieri, Gabriele Costa, Francesco La Torre, Fabio Martinelli, "Detection of images with adult content for parental control on mobile devices", In Proceedings of the 6th International Conference on Mobile Technology Application Systems Mobility 09 (2009), ISBN 9781605585369:1-5.
  9. Ethem Alpaydin," Introduction To Machine Learning ",The MIT Press Cambridge, Massachusetts London, England , ISBN: 0-262-01211-1 (hc),pp 133-139.
  10. M. K. Hu,"Visual problem recognition by moment invariant",IRE Transaction on Information Theory, Vol IT-8, pp 179-187,Feb 1962.
Index Terms

Computer Science
Information Sciences

Keywords

Image Segmentation Moment Based Clustering Misclassification Rate Mismatching Rate PSNR MSE

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