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Automatic Fault Detection in Mosquito Nets Using Machine Vision System

B. Venkatesan, K. Vedha Priya, S. Puja Srinidhi, T. Vignesh Prabhu

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


Keywords


Inspection System, Embedded Vision System, Image processing

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