Application of automated image analysis to the identification and extraction of recyclable plastic bottles

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13 Citations (Scopus)

Abstract

An experimental machine vision apparatus was used to identify and extract recyclable plastic bottles out of a conveyor belt. Color images were taken with a commercially available Webcam, and the recognition was performed by our homemade software, based on the shape and dimensions of object images. The software was able to manage multiple bottles in a single image and was additionally extended to cases involving touching bottles. The identification was fulfilled by comparing the set of measured features with an existing database and meanwhile integrating various recognition techniques such as minimum distance in the feature space, self-organized maps, and neural networks. The recognition system was tested on a set of 50 different bottles and provided so far an accuracy of about 97% on bottle identification. The extraction of the bottles was performed by means of a pneumatic arm, which was activated according to the plastic type; polyethylene-terephthalate (PET) bottles were left on the conveyor belt, while non-PET bottles were extracted. The software was designed to provide the best compromise between reliability and speed for real-time applications in view of the commercialization of the system at existing recycling plants.

Original languageEnglish
Pages (from-to)794-799
Number of pages6
JournalJournal of Zhejiang University: Science A
Volume10
Issue number6
DOIs
Publication statusPublished - Jun 2009

Fingerprint

Plastic bottles
Bottles
Image analysis
Pneumatics
Polyethylene terephthalates
Computer vision
Recycling
Plastics
Color
Neural networks

Keywords

  • Automated sorting
  • Computer vision
  • Pattern recognition
  • Recycling

ASJC Scopus subject areas

  • Engineering(all)

Cite this

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title = "Application of automated image analysis to the identification and extraction of recyclable plastic bottles",
abstract = "An experimental machine vision apparatus was used to identify and extract recyclable plastic bottles out of a conveyor belt. Color images were taken with a commercially available Webcam, and the recognition was performed by our homemade software, based on the shape and dimensions of object images. The software was able to manage multiple bottles in a single image and was additionally extended to cases involving touching bottles. The identification was fulfilled by comparing the set of measured features with an existing database and meanwhile integrating various recognition techniques such as minimum distance in the feature space, self-organized maps, and neural networks. The recognition system was tested on a set of 50 different bottles and provided so far an accuracy of about 97{\%} on bottle identification. The extraction of the bottles was performed by means of a pneumatic arm, which was activated according to the plastic type; polyethylene-terephthalate (PET) bottles were left on the conveyor belt, while non-PET bottles were extracted. The software was designed to provide the best compromise between reliability and speed for real-time applications in view of the commercialization of the system at existing recycling plants.",
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AU - Mustafa, Mohd. Marzuki

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