Automatic Fault Detection in Mosquito Nets Using Machine Vision System

Authors

  • B. Venkatesan Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Erode
  • K. Vedha Priya Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Erode
  • S. Puja Srinidhi Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Erode
  • T. Vignesh Prabhu Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Erode

DOI:

https://doi.org/10.37591/joosd.v6i2.2260

Keywords:

Inspection System, Embedded Vision System, Image processing

Abstract

Abstract

Mosquito-borne diseases are flourishing worldwide. Dengue viruses and malaria protozoa are of increasing global concern in public health as it causes series of health issues, particularly to the current generation. The possible solution is to use mosquito nets as a preventive measure. Mosquito nets are manufactured in large scale to provide protection from the infectious insects like mosquitoes. Manufactured nets are inspected using man power to find faults and errors, which is in­efficient and less accurate. This project is proposed to find a solution to eliminate manual errors and increase the accuracy. Machine vision system is an innovative low cost system, used to automate the fault inspection in mosquito nets. Embedded vision system is used to ensure product quality in a better way. A set of 50 images of net with no error and 75 images of nets with different type of errors are taken. The accuracy of 93.33% is achieved by using the proposed system.

 

 

Cite this Article

B. Venkatesan, K. Vedha Priya, S. Puja Srinidhi, T. Vignesh Prabhu. Automatic Fault Detection in Mosquito Nets Using Machine Vision System. Journal of Open Source Developments. 2019; 6(2): 6–11p

Downloads

Published

2019-09-06

Issue

Vol. 6 No. 2 (2019)

Section

Research Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.