Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products
Food processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important p...
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2018-01-01
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Online Access: | https://hrcak.srce.hr/file/311136 |
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doaj-e3d20f2ff5284c7aa272c0d4d2fde4a52020-11-25T02:13:28ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek Tehnički Vjesnik1330-36511848-63392018-01-0125617391745Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture ProductsDragan Markovic0Jelena Ilic1Vojislav Simonovic2Nenad Gubeljak3Emil Veg4Goran Šiniković5Ivana Markovic6Faculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaUniversity of Maribor, Facutly of Mechanical Engineering, Smetanova 17, 2000 Maribor, SloveniaFaculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaFaculty of Mechanical Engineering, Kraljcie Marije 16, 11000 Belgrade, SerbiaFood processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important product appearance attributes are color and texture. During food processing, the product is captured by optical devices, mostly color cameras and lasers. The aim of this paper is to investigate new eligibility criteria for digital image segmentation by using only image from the camera. The goal is to describe the texture of the product, based on chosen mathematical measures, and to allow for recognition and then classification according to the predefined range of values in an appropriate class. Images of frozen raspberry were used. Image analysis of color parameters in RGB color space and statistical tests to examine normality of data were carried out. Thereafter, one-way Anova and correlation analysis was performed. Statistically significant difference was found for the values of two indicators: entropy and new criteria were derived from standard deviation, as well as mean values of pixels for every channel, and marked as L. After determining the range of these criteria, a new algorithm was developed for image segmentation written in Matlab. One of the results of applying this algorithm is that more than 80% of good products were recognized.https://hrcak.srce.hr/file/311136colorfruitssegmentationsorting |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dragan Markovic Jelena Ilic Vojislav Simonovic Nenad Gubeljak Emil Veg Goran Šiniković Ivana Markovic |
spellingShingle |
Dragan Markovic Jelena Ilic Vojislav Simonovic Nenad Gubeljak Emil Veg Goran Šiniković Ivana Markovic Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products Tehnički Vjesnik color fruits segmentation sorting |
author_facet |
Dragan Markovic Jelena Ilic Vojislav Simonovic Nenad Gubeljak Emil Veg Goran Šiniković Ivana Markovic |
author_sort |
Dragan Markovic |
title |
Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products |
title_short |
Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products |
title_full |
Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products |
title_fullStr |
Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products |
title_full_unstemmed |
Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products |
title_sort |
application of statistical indicators for digital image analysis and segmentation in sorting of agriculture products |
publisher |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
series |
Tehnički Vjesnik |
issn |
1330-3651 1848-6339 |
publishDate |
2018-01-01 |
description |
Food processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important product appearance attributes are color and texture. During food processing, the product is captured by optical devices, mostly color cameras and lasers. The aim of this paper is to investigate new eligibility criteria for digital image segmentation by using only image from the camera. The goal is to describe the texture of the product, based on chosen mathematical measures, and to allow for recognition and then classification according to the predefined range of values in an appropriate class. Images of frozen raspberry were used. Image analysis of color parameters in RGB color space and statistical tests to examine normality of data were carried out. Thereafter, one-way Anova and correlation analysis was performed. Statistically significant difference was found for the values of two indicators: entropy and new criteria were derived from standard deviation, as well as mean values of pixels for every channel, and marked as L. After determining the range of these criteria, a new algorithm was developed for image segmentation written in Matlab. One of the results of applying this algorithm is that more than 80% of good products were recognized. |
topic |
color fruits segmentation sorting |
url |
https://hrcak.srce.hr/file/311136 |
work_keys_str_mv |
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