Intelligent computer vision system for segregating recyclable waste papers

Mohammad Osiur Rahman, Aini Hussain, Edgar Scavino, Hassan Basri, M. A. Hannan

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

This article explores the application of image processing techniques in recyclable waste paper sorting. In recycling, waste papers are segregated into various grades as they are subjected to different recycling processes. Highly sorted paper streams facilitate high quality end products and save processing chemicals and energy. From 1932 to 2009, different mechanical and optical paper sorting methods have been developed to fill the paper sorting demand. Still, in many countries including Malaysia, waste papers are sorted into different grades using a manual sorting system. Because of inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems has increased. Automated paper sorting systems offer significant advantages over human inspection in terms of worker fatigue, throughput, speed, and accuracy. This research attempts to develop a smart vision sensing system that is able to separate the different grades of paper using first-order features. To construct a template database, a statistical approach with intra-class and inter-class variation techniques are applied to the feature selection process. Finally, the K-nearest neighbor (KNN) algorithm is applied for paper object grade identification. The remarkable achievement obtained with the method is the accurate identification and dynamic sorting of all grades of papers using simple image processing techniques. © 2011 Published by Elsevier Ltd.
Original languageEnglish
Pages (from-to)10398-10407
Number of pages9357
JournalExpert Systems with Applications
DOIs
Publication statusPublished - 01 Aug 2011
Externally publishedYes

Fingerprint

Waste paper
computer vision
Sorting
sorting
Computer vision
image processing
Recycling
Image processing
recycling
Throughput
waste paper
fatigue
Feature extraction
Inspection
Fatigue of materials

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Energy(all)
  • Mechanical Engineering
  • Management, Monitoring, Policy and Law

Cite this

Rahman, Mohammad Osiur ; Hussain, Aini ; Scavino, Edgar ; Basri, Hassan ; Hannan, M. A. / Intelligent computer vision system for segregating recyclable waste papers. In: Expert Systems with Applications. 2011 ; pp. 10398-10407.
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Intelligent computer vision system for segregating recyclable waste papers. / Rahman, Mohammad Osiur; Hussain, Aini; Scavino, Edgar; Basri, Hassan; Hannan, M. A.

In: Expert Systems with Applications, 01.08.2011, p. 10398-10407.

Research output: Contribution to journalArticle

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