Development of Counting and Analysis Lemons System with Computer Vision Technology
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Abstract
This article presents development of counting and analysis lemons system with computer vision technology for test the performance of analysis system for color and counting of lemons to facilitate farmers. Firstly, designing the system and training the system with images of soft lemons and mature lemons 574 images, which image processing techniques were applied to this process. Then test the performance of the pressing system with 400 lemons. Divided into 200 soft lemons and 200 mature lemons. From the experiment counting of soft lemons system analysis accuracy 92% there is an error of 8% and counting of mature lemons system analysis accuracy 98% there is an error of 2% respectively.
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References
Tanut Bh. and Kamsuwan N., A Prototype Development of Marigold Classification by Image Processing, Journal Science and Technology Nakhon Sawan Rajabhat University. 2019; 11(13): 79-92.
Kajornlap W. and Janpho J., Lemon Size Sorting Machine, Thesis in Production Techniques. 2015.
Suksukont A., Santingamwong Ch., Khamkhaek W., Pansuwan S., Fruits Ripening Analysis System using Image Processing Technology, Journal of Information Science and Technology. 2022; 12(1): 61-66.
Priwthaisong K., Automatic Color Sorting Machine on Conveyor Systems Controlled by Arduino, Association of Privatr Higher Education Institutions of Thailand. 5(1); 2016: 15-21.
Pangerd S., Jeeranantasin N., Julakasemsak P., Cobal R., Duangmeun W., Automatic Mango Weight and Color Sorting Machine Equipped with Microcontrolle, Research Journal of Rajamangala University of Technology Krungthep. 2022; 16(2): 99-105.
Jing L., Junzheng W. and Jiali M., Color moving object Detection Method Based on Automatic Color Clustering, Proceedings of the 33rd Chinese Control Conference. July 28-30, 2014: 7232-7235.
Gokul P.R., Raj S. and Suriyamoorthi P., Estimation of Volume and Maturity of Sweet Lime Fruit using Image Processing Algorithm, International Conference on Communications and Signal Processing (ICCSP). April 2-4, 2015: 1227-1229.
Pandey C., Sethy P.K., Biswas P., Behera S.K. and Khan M.R., Quality Evaluation of Pomegranate Fruit using Image Processing Techniques, International Conference on Communication and Signal Processing (ICCSP). July 28-30, 2020: 38-40.
Sotirov S.I., Zhelyazkov S.P., Marudova M.G., Zsivanovits G. and Tokamkov D.M., Embedded System for Fruit Image Processing, International Scientific Conference Electronics. September 16-18, 2020: 1-3.