Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products
2018
Аутори
Marković, IvanaMarković, Dragan
Ilić, Jelena
Simonović, Vojislav
Veg, Emil
Šiniković, Goran
Gubeljak, Nenad
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
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 correlatio...n 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.
Кључне речи:
sorting / segmentation / fruits / colorИзвор:
Tehnički vjesnik, 2018, 25, 6, 1739-1745Издавач:
- Univ Osijek, Tech Fac, Slavonski Brod
Финансирање / пројекти:
- Истраживање и развој опреме и система за индустријску производњу, складиштење и прераду поврћа и воћа (RS-MESTD-Technological Development (TD or TR)-35043)
DOI: 10.17559/TV-20171129091703
ISSN: 1330-3651
WoS: 000453261600023
Scopus: 2-s2.0-85059418938
Институција/група
Mašinski fakultetTY - JOUR AU - Marković, Ivana AU - Marković, Dragan AU - Ilić, Jelena AU - Simonović, Vojislav AU - Veg, Emil AU - Šiniković, Goran AU - Gubeljak, Nenad PY - 2018 UR - https://machinery.mas.bg.ac.rs/handle/123456789/2899 AB - 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. PB - Univ Osijek, Tech Fac, Slavonski Brod T2 - Tehnički vjesnik T1 - Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products EP - 1745 IS - 6 SP - 1739 VL - 25 DO - 10.17559/TV-20171129091703 ER -
@article{ author = "Marković, Ivana and Marković, Dragan and Ilić, Jelena and Simonović, Vojislav and Veg, Emil and Šiniković, Goran and Gubeljak, Nenad", year = "2018", abstract = "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.", publisher = "Univ Osijek, Tech Fac, Slavonski Brod", journal = "Tehnički vjesnik", title = "Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products", pages = "1745-1739", number = "6", volume = "25", doi = "10.17559/TV-20171129091703" }
Marković, I., Marković, D., Ilić, J., Simonović, V., Veg, E., Šiniković, G.,& Gubeljak, N.. (2018). Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products. in Tehnički vjesnik Univ Osijek, Tech Fac, Slavonski Brod., 25(6), 1739-1745. https://doi.org/10.17559/TV-20171129091703
Marković I, Marković D, Ilić J, Simonović V, Veg E, Šiniković G, Gubeljak N. Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products. in Tehnički vjesnik. 2018;25(6):1739-1745. doi:10.17559/TV-20171129091703 .
Marković, Ivana, Marković, Dragan, Ilić, Jelena, Simonović, Vojislav, Veg, Emil, Šiniković, Goran, Gubeljak, Nenad, "Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products" in Tehnički vjesnik, 25, no. 6 (2018):1739-1745, https://doi.org/10.17559/TV-20171129091703 . .