An automatic sorting system for recycling beverage cans using the eigenface algorithm

I. Yani, E. Scavino, Hannan M A, Dzuraidah Abd. Wahab, Hassan Basri

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

Abstract

This paper describes the prototype implementation of a real-time automatic identification and sorting system for recyclable beverage cans using an intelligent computer vision technique. The image recognition system was developed based on the eigenface algorithm and achieved its ability to identify and sort by means of an automatic learning process. Three experiments have been conducted based on position and types of beverage cans moving on a conveyor belt. The results show that the identification and sorting of beverage cans achieved with an accuracy of up to 95%. It is concluded that the performance of the proposed system is robust enough for commercial applications.

Original languageEnglish
Title of host publicationCivil-Comp Proceedings
Volume103
Publication statusPublished - 2013
Event3rd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013 - Cagliari, Sardinia
Duration: 3 Sep 20136 Sep 2013

Other

Other3rd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013
CityCagliari, Sardinia
Period3/9/136/9/13

Fingerprint

Beverages
Sorting
Recycling
Image recognition
Computer vision
Experiments

Keywords

  • Automatic sorting
  • Beverage cans
  • Detection
  • Eigenface
  • Pattern recognition

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Civil and Structural Engineering
  • Artificial Intelligence
  • Environmental Engineering

Cite this

Yani, I., Scavino, E., M A, H., Abd. Wahab, D., & Basri, H. (2013). An automatic sorting system for recycling beverage cans using the eigenface algorithm. In Civil-Comp Proceedings (Vol. 103)

An automatic sorting system for recycling beverage cans using the eigenface algorithm. / Yani, I.; Scavino, E.; M A, Hannan; Abd. Wahab, Dzuraidah; Basri, Hassan.

Civil-Comp Proceedings. Vol. 103 2013.

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

Yani, I, Scavino, E, M A, H, Abd. Wahab, D & Basri, H 2013, An automatic sorting system for recycling beverage cans using the eigenface algorithm. in Civil-Comp Proceedings. vol. 103, 3rd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013, Cagliari, Sardinia, 3/9/13.
@inproceedings{600822db48ab4cfe8e4959bb1a8b73af,
title = "An automatic sorting system for recycling beverage cans using the eigenface algorithm",
abstract = "This paper describes the prototype implementation of a real-time automatic identification and sorting system for recyclable beverage cans using an intelligent computer vision technique. The image recognition system was developed based on the eigenface algorithm and achieved its ability to identify and sort by means of an automatic learning process. Three experiments have been conducted based on position and types of beverage cans moving on a conveyor belt. The results show that the identification and sorting of beverage cans achieved with an accuracy of up to 95{\%}. It is concluded that the performance of the proposed system is robust enough for commercial applications.",
keywords = "Automatic sorting, Beverage cans, Detection, Eigenface, Pattern recognition",
author = "I. Yani and E. Scavino and {M A}, Hannan and {Abd. Wahab}, Dzuraidah and Hassan Basri",
year = "2013",
language = "English",
isbn = "9781905088584",
volume = "103",
booktitle = "Civil-Comp Proceedings",

}

TY - GEN

T1 - An automatic sorting system for recycling beverage cans using the eigenface algorithm

AU - Yani, I.

AU - Scavino, E.

AU - M A, Hannan

AU - Abd. Wahab, Dzuraidah

AU - Basri, Hassan

PY - 2013

Y1 - 2013

N2 - This paper describes the prototype implementation of a real-time automatic identification and sorting system for recyclable beverage cans using an intelligent computer vision technique. The image recognition system was developed based on the eigenface algorithm and achieved its ability to identify and sort by means of an automatic learning process. Three experiments have been conducted based on position and types of beverage cans moving on a conveyor belt. The results show that the identification and sorting of beverage cans achieved with an accuracy of up to 95%. It is concluded that the performance of the proposed system is robust enough for commercial applications.

AB - This paper describes the prototype implementation of a real-time automatic identification and sorting system for recyclable beverage cans using an intelligent computer vision technique. The image recognition system was developed based on the eigenface algorithm and achieved its ability to identify and sort by means of an automatic learning process. Three experiments have been conducted based on position and types of beverage cans moving on a conveyor belt. The results show that the identification and sorting of beverage cans achieved with an accuracy of up to 95%. It is concluded that the performance of the proposed system is robust enough for commercial applications.

KW - Automatic sorting

KW - Beverage cans

KW - Detection

KW - Eigenface

KW - Pattern recognition

UR - http://www.scopus.com/inward/record.url?scp=84894136108&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84894136108&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84894136108

SN - 9781905088584

VL - 103

BT - Civil-Comp Proceedings

ER -