1. Valous NA, Sun DW. Image processing techniques for computer vision in the food and beverage industries. Computer Vision Technology in the Food and Beverage Industries; 2012:97-129. [
DOI:10.1533/9780857095770.1.97]
2. Turgut SS, Karacabey E, Küçüköner E. Potential of image analysis based systems in food quality assessments and classifications. Presented at:. Proceedings of the 9th Baltic Conference on Food Science and Technology "Food for Consumer Well-Being" FOODBALT. Jelgava, Latvia, May 8-9, 2014.
3. Du CJ, Sun DW. Learning techniques used in computer vision for food quality evaluation: A review. J Food Eng. 2006;72:39-55. doi: 10.1016/j.jfoodeng.2004.11.017.. [
DOI:10.1016/j.jfoodeng.2004.11.017]
4. Patrício DI, Rieder R. Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review. Comput Electron Agric. 2018;153:69-81 doi: 10.1016/j.compag.2018.08.001. [
DOI:10.1016/j.compag.2018.08.001]
5. Lopes JF, Ludwig L, Barbin DF, Grossmann MVE, Barbon S Jr. Computer vision classification of barley flour based on spatial pyramid partition ensemble. Sensors (Basel). 2019;19(13). pii: E2953. doi: 10.3390/s19132953. [
DOI:10.3390/s19132953]
6. Colyer SL, Evans M, Cosker DP, Salo AIT. A review of the evolution of vision-based motion analysis and the integration of advanced computer vision methods towards developing a markerless system. Sports Med Open. 2018;4(1):24. doi: 10.1186/s40798-018-0139-y.. [
DOI:10.1186/s40798-018-0139-y]
7. Patel KK, Kar A, Jha SN, Khan MA. Machine vision system: a tool for quality inspection of food and agricultural products. J Food Sci Technol. 2012;49(2):123-141. doi: 10.1007/s13197-011-0321-4. [
DOI:10.1007/s13197-011-0321-4]
8. Hajizadeh M, Kasraei M. Grading walnut using a vision machine and special mass [in Persian]. Presented at: Proceedings of the 5th National Congress on Agricultural Machinery and Mechanization. Mashhad, Iran, August 6-7,1999.
9. Tao Y, Morrow CT, Heinemann PH, Sommer III HJ. Fourier-based separation technique for shape grading of potatoes using machine vision. Transactions of the American Society of Agricultural Engineers. 1995;38(3):949-957. doi: 10.13031/2013.27912. [
DOI:10.13031/2013.27912]
10. Lee DJ, Archibald JK, Chang YC, Greco CR. Robust color space conversion and color distribution analysis techniques for date maturity evaluation. J Food Eng. 2008;88(3):364-372. [
DOI:10.1016/j.jfoodeng.2008.02.023]
11. Lee DJ, Schoenberger R, Archibald J, McCollum S. Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging. J Food Eng. 2008;86(3):388-398. [
DOI:10.1016/j.jfoodeng.2007.10.021]
12. Jarimopas B, Jaisin N. An experimental machine vision system for sorting sweet tamarind. J Food Eng. 2008;89(3):291-297. [
DOI:10.1016/j.jfoodeng.2008.05.007]
13. Fayyazi S, Abbaspourfard MH, Rohani A, Sadrnia H, Monadjemi SAH. Identification and classification of three Iranian rice seed varieties in mixed samples by morphological features using image processing and Learning Vector Quantization neural network [in Persian]. Iranian Food Scie Technol Res J. 2014;10(3):211-218.
14. Blasco J, Munera S, Aleixos N, Cubero S, Molto E. Machine vision-based measurement systems for fruit and vegetable quality control in postharvest. Adv Biochem Eng Biotechnol. 2017;161:71-91. doi: 10.1007/10_2016_51. [
DOI:10.1007/10_2016_51]
15. Mohamad Kazemi F, Panahi Laein F. The evaluation of the color of mangos for grading its quality using image processing [in Persian]. Presented at: Proceedings of the 1st Conference of Computer Systems Intelligent Systems and Their Applications. Tehran, Iran, Payame Noor University, November 30 2011.
16. Mozafari H, Rahmani H. Using image processing for grading Piarom date [in Persian]. Presented at: Proceedings of the National Conference of Iranian Date; Kerman, Iran, September 2-3, 2012.
17. Rahmani H, Naeini SN, Nezam Abadipour H, Ahmadi E. The feasibility of using image processing to detect maladaptive date defects [in Persian]. Presented at: Proceedings of the 6th National Congress of Agricultural Machinery and Mechanization of Campus Agriculture and Natural Resources University of Tehran, Tehran, Iran, September 13-14, 2010.