Abstract

The removal of plastic contamination from cotton lint is an issue of top priority to the U.S. cotton industry. One of the main sources of plastic contamination showing up in marketable cotton bales is plastic used to wrap cotton modules produced by John Deere round module harvesters. Despite diligent efforts by cotton ginning personnel to remove all plastic encountered during module unwrapping, plastic still finds a way into the cotton gin’s processing system. To help mitigate plastic contamination at the gin, a machine-vision detection and removal system was developed that utilizes low-cost color cameras to see plastic coming down the gin-stand feeder apron, which upon detection, blows plastic out of the cotton stream to prevent contamination. This paper presents the software design of this inspection and removal system. The system was tested throughout the entire 2019 cotton ginning season at two commercial cotton gins and at one gin in the 2018 ginning season. The focus of this report is to describe the software design and discuss relevant issues that influenced the design of the software.

Highlights

  • IntroductionThe removal of plastic contamination in cotton lint is an issue of top priority to the

  • Background Development ToolsThe software discussed in this technical note provides a monitoring–ejection system of the gin-stand feeder apron for the ginners

  • As most cotton gins have their networks configured behind a router that employs network address translation (NAT); in order to access the nodes remotely for monitoring and management, each node was set up with a reverse SSH tunnel acting through a cloud-based server that acted as an intermediary that would forward the connection for remote administration

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Summary

Introduction

The removal of plastic contamination in cotton lint is an issue of top priority to the. Current data shows U.S cotton is trading at a USD 0.01/kg discount, relative to the market for a total loss of USD 0.034/kg with respect to market conditions prior to wide-spread adoption of plastic-wrapped cotton modules [2,3]. Extrapolating this loss of premium out across the annual cotton yield for a typical year in the United States; the cost of this loss to U.S producers is in excess of USD 750 million annually.

Module
Gin-stand
Under-side of the installation with with aa bank bank of of 12
Plastic
Background Development Tools
Node Control Interface
User Interface
11. Screenshot
Lab Color Space
Negative Classifier Look-Up Table
Building the Negative Classifier
19. The negative classifier dialog thatdisplays displays when “Build or “Append
Image Processing for Plastic Detection
3.10. Open-Source Libraries
Software Design Summary
Conclusions
Findings
Full Text
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