Imаge Segmentation Of Agricultural Products Using Statistical Indicators
2020
Autori
Medojević, IvanaMarković, Dragan
Simonović, Vojislav
Ilić, Jelena
Joksimović, Aleksandra
Veg, Emil
Ostala autorstva
Popov, GeorgiOvtcharova, Jivka
Konferencijski prilog (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Machine inspection is a mandatory technological process in industrial processing agriculture products. The camera detects color and shape based irregularities of the object resulting in a large number of parameters for decision-making and sorting product compliance. The goal was to discover a new criterion for decision-making using only the output signal of the RGB camera. Research employed the digital images of raspberries, blackberries, peas and yellow beans during real processing, obtained from a color sorter machine. The visual texture of the surface of the agricultural products was described via defined statistical indicators of color (color average value (Avg), standard deviation (Stdv), entropy (E), and lacunarity (L) was used from the sphere of image fractal analysis as one of the criteria. By applying the non-parametric tests: Wilcoxon signed rank and Friedman test, statistically significant difference was established for the L and Е criteria between compliant and non-complian...t industrial products
Ključne reči:
color / agricultural product sorting / machine visionIzvor:
Proceedings Industry 4.0. V International Scientific Conference - Winter Session, 2020, 2, 155-160Izdavač:
- SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"
Finansiranje / projekti:
- Istraživanje i razvoj opreme i sistema za industrijsku proizvodnju, skladištenje i preradu povrća i voća (RS-MESTD-Technological Development (TD or TR)-35043)
Institucija/grupa
Mašinski fakultetTY - CONF AU - Medojević, Ivana AU - Marković, Dragan AU - Simonović, Vojislav AU - Ilić, Jelena AU - Joksimović, Aleksandra AU - Veg, Emil PY - 2020 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4671 AB - Machine inspection is a mandatory technological process in industrial processing agriculture products. The camera detects color and shape based irregularities of the object resulting in a large number of parameters for decision-making and sorting product compliance. The goal was to discover a new criterion for decision-making using only the output signal of the RGB camera. Research employed the digital images of raspberries, blackberries, peas and yellow beans during real processing, obtained from a color sorter machine. The visual texture of the surface of the agricultural products was described via defined statistical indicators of color (color average value (Avg), standard deviation (Stdv), entropy (E), and lacunarity (L) was used from the sphere of image fractal analysis as one of the criteria. By applying the non-parametric tests: Wilcoxon signed rank and Friedman test, statistically significant difference was established for the L and Е criteria between compliant and non-compliant industrial products PB - SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0" C3 - Proceedings Industry 4.0. V International Scientific Conference - Winter Session T1 - Imаge Segmentation Of Agricultural Products Using Statistical Indicators EP - 160 SP - 155 VL - 2 UR - https://hdl.handle.net/21.15107/rcub_machinery_4671 ER -
@conference{ author = "Medojević, Ivana and Marković, Dragan and Simonović, Vojislav and Ilić, Jelena and Joksimović, Aleksandra and Veg, Emil", year = "2020", abstract = "Machine inspection is a mandatory technological process in industrial processing agriculture products. The camera detects color and shape based irregularities of the object resulting in a large number of parameters for decision-making and sorting product compliance. The goal was to discover a new criterion for decision-making using only the output signal of the RGB camera. Research employed the digital images of raspberries, blackberries, peas and yellow beans during real processing, obtained from a color sorter machine. The visual texture of the surface of the agricultural products was described via defined statistical indicators of color (color average value (Avg), standard deviation (Stdv), entropy (E), and lacunarity (L) was used from the sphere of image fractal analysis as one of the criteria. By applying the non-parametric tests: Wilcoxon signed rank and Friedman test, statistically significant difference was established for the L and Е criteria between compliant and non-compliant industrial products", publisher = "SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"", journal = "Proceedings Industry 4.0. V International Scientific Conference - Winter Session", title = "Imаge Segmentation Of Agricultural Products Using Statistical Indicators", pages = "160-155", volume = "2", url = "https://hdl.handle.net/21.15107/rcub_machinery_4671" }
Medojević, I., Marković, D., Simonović, V., Ilić, J., Joksimović, A.,& Veg, E.. (2020). Imаge Segmentation Of Agricultural Products Using Statistical Indicators. in Proceedings Industry 4.0. V International Scientific Conference - Winter Session SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"., 2, 155-160. https://hdl.handle.net/21.15107/rcub_machinery_4671
Medojević I, Marković D, Simonović V, Ilić J, Joksimović A, Veg E. Imаge Segmentation Of Agricultural Products Using Statistical Indicators. in Proceedings Industry 4.0. V International Scientific Conference - Winter Session. 2020;2:155-160. https://hdl.handle.net/21.15107/rcub_machinery_4671 .
Medojević, Ivana, Marković, Dragan, Simonović, Vojislav, Ilić, Jelena, Joksimović, Aleksandra, Veg, Emil, "Imаge Segmentation Of Agricultural Products Using Statistical Indicators" in Proceedings Industry 4.0. V International Scientific Conference - Winter Session, 2 (2020):155-160, https://hdl.handle.net/21.15107/rcub_machinery_4671 .