Segregating recyclable waste papers using co-occurrence features

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper 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 will facilitate high quality end products, and save processing chemicals and energy. Since 1932 to 2009, different mechanical and optical paper sorting methods have been developed to fill the demand of paper sorting. Still, in many countries including Malaysia, waste papers are sorted into different grades using manual sorting system. Due to inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems is increased. Automated paper sorting systems offer significant advantages over human inspection in terms of fatigue, throughput, speed, and accuracy. This research attempts to develop a smart vision sensing system that able to separate the different grades of paper using co-occurrence features. Finally, the rule based classifier is applied for paper object grade identification. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 92%, 89% and 91%, respectively.

Original languageEnglish
Title of host publicationProceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09
Pages157-162
Number of pages6
Publication statusPublished - 2009
Event9th WSEAS International Conference on Applied Computer Science, ACS '09 - Genova
Duration: 17 Oct 200919 Oct 2009

Other

Other9th WSEAS International Conference on Applied Computer Science, ACS '09
CityGenova
Period17/10/0919/10/09

Fingerprint

Waste paper
Sorting
Recycling
Throughput
Malaysia
Newsprint
Fatigue
Inspection
Image Processing
Image processing
Classifiers
Sensing
Classifier
Fatigue of materials
Processing
Energy

Keywords

  • Co-occurrence matrix
  • Grades of paper
  • Waste paper recycling
  • Waste paper sorting

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Rahman, M. O., Hussain, A., Scavino, E., M A, H., & Basri, H. (2009). Segregating recyclable waste papers using co-occurrence features. In Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09 (pp. 157-162)

Segregating recyclable waste papers using co-occurrence features. / Rahman, Mohammad Osiur; Hussain, Aini; Scavino, Edgar; M A, Hannan; Basri, Hassan.

Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09. 2009. p. 157-162.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rahman, MO, Hussain, A, Scavino, E, M A, H & Basri, H 2009, Segregating recyclable waste papers using co-occurrence features. in Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09. pp. 157-162, 9th WSEAS International Conference on Applied Computer Science, ACS '09, Genova, 17/10/09.
Rahman MO, Hussain A, Scavino E, M A H, Basri H. Segregating recyclable waste papers using co-occurrence features. In Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09. 2009. p. 157-162
Rahman, Mohammad Osiur ; Hussain, Aini ; Scavino, Edgar ; M A, Hannan ; Basri, Hassan. / Segregating recyclable waste papers using co-occurrence features. Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09. 2009. pp. 157-162
@inproceedings{a3e8910d39924034b0bc5de91bec4771,
title = "Segregating recyclable waste papers using co-occurrence features",
abstract = "This paper 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 will facilitate high quality end products, and save processing chemicals and energy. Since 1932 to 2009, different mechanical and optical paper sorting methods have been developed to fill the demand of paper sorting. Still, in many countries including Malaysia, waste papers are sorted into different grades using manual sorting system. Due to inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems is increased. Automated paper sorting systems offer significant advantages over human inspection in terms of fatigue, throughput, speed, and accuracy. This research attempts to develop a smart vision sensing system that able to separate the different grades of paper using co-occurrence features. Finally, the rule based classifier is applied for paper object grade identification. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 92{\%}, 89{\%} and 91{\%}, respectively.",
keywords = "Co-occurrence matrix, Grades of paper, Waste paper recycling, Waste paper sorting",
author = "Rahman, {Mohammad Osiur} and Aini Hussain and Edgar Scavino and {M A}, Hannan and Hassan Basri",
year = "2009",
language = "English",
isbn = "9789604741274",
pages = "157--162",
booktitle = "Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09",

}

TY - GEN

T1 - Segregating recyclable waste papers using co-occurrence features

AU - Rahman, Mohammad Osiur

AU - Hussain, Aini

AU - Scavino, Edgar

AU - M A, Hannan

AU - Basri, Hassan

PY - 2009

Y1 - 2009

N2 - This paper 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 will facilitate high quality end products, and save processing chemicals and energy. Since 1932 to 2009, different mechanical and optical paper sorting methods have been developed to fill the demand of paper sorting. Still, in many countries including Malaysia, waste papers are sorted into different grades using manual sorting system. Due to inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems is increased. Automated paper sorting systems offer significant advantages over human inspection in terms of fatigue, throughput, speed, and accuracy. This research attempts to develop a smart vision sensing system that able to separate the different grades of paper using co-occurrence features. Finally, the rule based classifier is applied for paper object grade identification. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 92%, 89% and 91%, respectively.

AB - This paper 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 will facilitate high quality end products, and save processing chemicals and energy. Since 1932 to 2009, different mechanical and optical paper sorting methods have been developed to fill the demand of paper sorting. Still, in many countries including Malaysia, waste papers are sorted into different grades using manual sorting system. Due to inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems is increased. Automated paper sorting systems offer significant advantages over human inspection in terms of fatigue, throughput, speed, and accuracy. This research attempts to develop a smart vision sensing system that able to separate the different grades of paper using co-occurrence features. Finally, the rule based classifier is applied for paper object grade identification. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 92%, 89% and 91%, respectively.

KW - Co-occurrence matrix

KW - Grades of paper

KW - Waste paper recycling

KW - Waste paper sorting

UR - http://www.scopus.com/inward/record.url?scp=78149291426&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78149291426&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:78149291426

SN - 9789604741274

SP - 157

EP - 162

BT - Proceedings of the 9th WSEAS International Conference on Applied Computer Science, ACS '09

ER -