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Design of Automatic Vision-based Inspection System for Monitoring in an Olive Oil Bottling Line

by Slim Abdelhedi, Khaled Taouil, Bassem Hadjkacem
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 51 - Number 21
Year of Publication: 2012
Authors: Slim Abdelhedi, Khaled Taouil, Bassem Hadjkacem
10.5120/8330-1968

Slim Abdelhedi, Khaled Taouil, Bassem Hadjkacem . Design of Automatic Vision-based Inspection System for Monitoring in an Olive Oil Bottling Line. International Journal of Computer Applications. 51, 21 ( August 2012), 39-46. DOI=10.5120/8330-1968

@article{ 10.5120/8330-1968,
author = { Slim Abdelhedi, Khaled Taouil, Bassem Hadjkacem },
title = { Design of Automatic Vision-based Inspection System for Monitoring in an Olive Oil Bottling Line },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 51 },
number = { 21 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 39-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume51/number21/8330-1968/ },
doi = { 10.5120/8330-1968 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:50:58.291825+05:30
%A Slim Abdelhedi
%A Khaled Taouil
%A Bassem Hadjkacem
%T Design of Automatic Vision-based Inspection System for Monitoring in an Olive Oil Bottling Line
%J International Journal of Computer Applications
%@ 0975-8887
%V 51
%N 21
%P 39-46
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automated vision inspection has become a vital part of the quality monitoring process. This paper compares the development and performance of two methodologies for a machine vision inspection system online for high speed conveyor. The first method developed is the Thresholding technique image processing algorithms and the second method is based on the edge detection. A case study was conducted to benchmark these two methods. Special effort has been put in the design of the defect detection algorithms to reach two main objectives: accurate feature extraction and on-line capabilities, both considering robustness and low processing time. An on-line implementation to inspect bottles is reported using new communication technique with GigE Vision camera and industrial Gigabit Ethernet network. The system is validated on olive oil bed. The implementation of our algorithm results in an effective real-time object tracking. The validity of the approach is illustrated by the presentation of experiment results obtained using the methods described in this paper.

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Index Terms

Computer Science
Information Sciences

Keywords

GigE vision camera Image processing Quality Monitoring Defects detection

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