Recyclable waste paper sorting using template matching

Mohammad Osiur Rahman, Aini Hussain, Edgar Scavino, M. A. Hannan, 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 Template Matching. For constructing template database, the RGB components of the pixel values are used to construct RGBString for template images. Finally, paper object grade is identified based on the maximum occurrence of a specific template image in the search image. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 96%, 92% and 96%, respectively. The remarkable achievement obtained with the method is the accurate identification and dynamic sorting of all grades of papers using simple image processing techniques. © 2009 Springer-Verlag.
Original languageEnglish
Title of host publicationRecyclable waste paper sorting using template matching
Pages467-478
Number of pages419
ISBN (Electronic)3642050352, 9783642050350
DOIs
Publication statusPublished - 01 Dec 2009
Externally publishedYes
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 11 Nov 2013 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5857 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period11/11/13 → …

Fingerprint

Waste paper
Template matching
Sorting
Recycling
Image processing
Throughput
Newsprint
Inspection
Pixels
Fatigue of materials

Cite this

Osiur Rahman, M., Hussain, A., Scavino, E., Hannan, M. A., & Basri, H. (2009). Recyclable waste paper sorting using template matching. In Recyclable waste paper sorting using template matching (pp. 467-478). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS). https://doi.org/10.1007/978-3-642-05036-7_44
Osiur Rahman, Mohammad ; Hussain, Aini ; Scavino, Edgar ; Hannan, M. A. ; Basri, Hassan. / Recyclable waste paper sorting using template matching. Recyclable waste paper sorting using template matching. 2009. pp. 467-478 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{b412fb2d170649c88519086ff7ea6fe3,
title = "Recyclable waste paper sorting using template matching",
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 Template Matching. For constructing template database, the RGB components of the pixel values are used to construct RGBString for template images. Finally, paper object grade is identified based on the maximum occurrence of a specific template image in the search image. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 96{\%}, 92{\%} and 96{\%}, respectively. The remarkable achievement obtained with the method is the accurate identification and dynamic sorting of all grades of papers using simple image processing techniques. {\circledC} 2009 Springer-Verlag.",
author = "{Osiur Rahman}, Mohammad and Aini Hussain and Edgar Scavino and Hannan, {M. A.} and Hassan Basri",
year = "2009",
month = "12",
day = "1",
doi = "10.1007/978-3-642-05036-7_44",
language = "English",
isbn = "3642050352",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "467--478",
booktitle = "Recyclable waste paper sorting using template matching",

}

Osiur Rahman, M, Hussain, A, Scavino, E, Hannan, MA & Basri, H 2009, Recyclable waste paper sorting using template matching. in Recyclable waste paper sorting using template matching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5857 LNCS, pp. 467-478, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11/11/13. https://doi.org/10.1007/978-3-642-05036-7_44

Recyclable waste paper sorting using template matching. / Osiur Rahman, Mohammad; Hussain, Aini; Scavino, Edgar; Hannan, M. A.; Basri, Hassan.

Recyclable waste paper sorting using template matching. 2009. p. 467-478 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS).

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

TY - GEN

T1 - Recyclable waste paper sorting using template matching

AU - Osiur Rahman, Mohammad

AU - Hussain, Aini

AU - Scavino, Edgar

AU - Hannan, M. A.

AU - Basri, Hassan

PY - 2009/12/1

Y1 - 2009/12/1

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 Template Matching. For constructing template database, the RGB components of the pixel values are used to construct RGBString for template images. Finally, paper object grade is identified based on the maximum occurrence of a specific template image in the search image. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 96%, 92% and 96%, respectively. The remarkable achievement obtained with the method is the accurate identification and dynamic sorting of all grades of papers using simple image processing techniques. © 2009 Springer-Verlag.

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 Template Matching. For constructing template database, the RGB components of the pixel values are used to construct RGBString for template images. Finally, paper object grade is identified based on the maximum occurrence of a specific template image in the search image. The outcomes from the experiment in classification for White Paper, Old Newsprint Paper and Old Corrugated Cardboard are 96%, 92% and 96%, respectively. The remarkable achievement obtained with the method is the accurate identification and dynamic sorting of all grades of papers using simple image processing techniques. © 2009 Springer-Verlag.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=76549098901&origin=inward

UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=76549098901&origin=inward

U2 - 10.1007/978-3-642-05036-7_44

DO - 10.1007/978-3-642-05036-7_44

M3 - Conference contribution

SN - 3642050352

SN - 9783642050350

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 467

EP - 478

BT - Recyclable waste paper sorting using template matching

ER -

Osiur Rahman M, Hussain A, Scavino E, Hannan MA, Basri H. Recyclable waste paper sorting using template matching. In Recyclable waste paper sorting using template matching. 2009. p. 467-478. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-05036-7_44