Vision-based egg grade classifier

Mohd Zin Zalhan, Sera Syarmila Sameon, Ismail Mohd Nazri, Ismail Mohd Taha

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

2 Citations (Scopus)

Abstract

Digital image processing techniques (DIP) have been widely used in various types of application recently. A variety of these techniques are now being used in many types of application area such as object classification, intelligent system, robotics, biometrics system, medical visualization, military, law enforcement, image enhancement and restoration, industrial inspection, artistic effect and human computer interfaces. This paper proposes the implementation of digital image processing techniques to classify three different categories of commercial eggs. The proposed system consists of the study on different types and sizes of commercial eggs, real size measurement of these eggs using Coordinate Measure Machine (CMM) and camera, classification algorithm and the development of vision based egg classification system. Image processing techniques such as image filtering and image enhancements have been applied in the system. Results have shown that the proposed system has been able to successfully classify three categories of commercial eggs with accuracy of more than 96%.

Original languageEnglish
Title of host publicationICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-35
Number of pages5
ISBN (Electronic)9781509004126
DOIs
Publication statusPublished - 30 Mar 2017
Event1st International Conference on Information and Communication Technology, ICICTM 2016 - Kuala Lumpur, Malaysia
Duration: 16 May 201617 May 2016

Other

Other1st International Conference on Information and Communication Technology, ICICTM 2016
CountryMalaysia
CityKuala Lumpur
Period16/05/1617/05/16

Fingerprint

Image processing
Classifiers
Image enhancement
Law enforcement
Intelligent systems
Biometrics
Image reconstruction
Interfaces (computer)
Robotics
Visualization
Inspection
Cameras

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Zalhan, M. Z., Sameon, S. S., Mohd Nazri, I., & Mohd Taha, I. (2017). Vision-based egg grade classifier. In ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology (pp. 31-35). [7890772] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICICTM.2016.7890772
Zalhan, Mohd Zin ; Sameon, Sera Syarmila ; Mohd Nazri, Ismail ; Mohd Taha, Ismail. / Vision-based egg grade classifier. ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 31-35
@inproceedings{c3d6ea388e7843ab98b7343075c11f70,
title = "Vision-based egg grade classifier",
abstract = "Digital image processing techniques (DIP) have been widely used in various types of application recently. A variety of these techniques are now being used in many types of application area such as object classification, intelligent system, robotics, biometrics system, medical visualization, military, law enforcement, image enhancement and restoration, industrial inspection, artistic effect and human computer interfaces. This paper proposes the implementation of digital image processing techniques to classify three different categories of commercial eggs. The proposed system consists of the study on different types and sizes of commercial eggs, real size measurement of these eggs using Coordinate Measure Machine (CMM) and camera, classification algorithm and the development of vision based egg classification system. Image processing techniques such as image filtering and image enhancements have been applied in the system. Results have shown that the proposed system has been able to successfully classify three categories of commercial eggs with accuracy of more than 96{\%}.",
author = "Zalhan, {Mohd Zin} and Sameon, {Sera Syarmila} and {Mohd Nazri}, Ismail and {Mohd Taha}, Ismail",
year = "2017",
month = "3",
day = "30",
doi = "10.1109/ICICTM.2016.7890772",
language = "English",
pages = "31--35",
booktitle = "ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

Zalhan, MZ, Sameon, SS, Mohd Nazri, I & Mohd Taha, I 2017, Vision-based egg grade classifier. in ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology., 7890772, Institute of Electrical and Electronics Engineers Inc., pp. 31-35, 1st International Conference on Information and Communication Technology, ICICTM 2016, Kuala Lumpur, Malaysia, 16/05/16. https://doi.org/10.1109/ICICTM.2016.7890772

Vision-based egg grade classifier. / Zalhan, Mohd Zin; Sameon, Sera Syarmila; Mohd Nazri, Ismail; Mohd Taha, Ismail.

ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology. Institute of Electrical and Electronics Engineers Inc., 2017. p. 31-35 7890772.

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

TY - GEN

T1 - Vision-based egg grade classifier

AU - Zalhan, Mohd Zin

AU - Sameon, Sera Syarmila

AU - Mohd Nazri, Ismail

AU - Mohd Taha, Ismail

PY - 2017/3/30

Y1 - 2017/3/30

N2 - Digital image processing techniques (DIP) have been widely used in various types of application recently. A variety of these techniques are now being used in many types of application area such as object classification, intelligent system, robotics, biometrics system, medical visualization, military, law enforcement, image enhancement and restoration, industrial inspection, artistic effect and human computer interfaces. This paper proposes the implementation of digital image processing techniques to classify three different categories of commercial eggs. The proposed system consists of the study on different types and sizes of commercial eggs, real size measurement of these eggs using Coordinate Measure Machine (CMM) and camera, classification algorithm and the development of vision based egg classification system. Image processing techniques such as image filtering and image enhancements have been applied in the system. Results have shown that the proposed system has been able to successfully classify three categories of commercial eggs with accuracy of more than 96%.

AB - Digital image processing techniques (DIP) have been widely used in various types of application recently. A variety of these techniques are now being used in many types of application area such as object classification, intelligent system, robotics, biometrics system, medical visualization, military, law enforcement, image enhancement and restoration, industrial inspection, artistic effect and human computer interfaces. This paper proposes the implementation of digital image processing techniques to classify three different categories of commercial eggs. The proposed system consists of the study on different types and sizes of commercial eggs, real size measurement of these eggs using Coordinate Measure Machine (CMM) and camera, classification algorithm and the development of vision based egg classification system. Image processing techniques such as image filtering and image enhancements have been applied in the system. Results have shown that the proposed system has been able to successfully classify three categories of commercial eggs with accuracy of more than 96%.

UR - http://www.scopus.com/inward/record.url?scp=85018365049&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018365049&partnerID=8YFLogxK

U2 - 10.1109/ICICTM.2016.7890772

DO - 10.1109/ICICTM.2016.7890772

M3 - Conference contribution

SP - 31

EP - 35

BT - ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Zalhan MZ, Sameon SS, Mohd Nazri I, Mohd Taha I. Vision-based egg grade classifier. In ICICTM 2016 - Proceedings of the 1st International Conference on Information and Communication Technology. Institute of Electrical and Electronics Engineers Inc. 2017. p. 31-35. 7890772 https://doi.org/10.1109/ICICTM.2016.7890772