Apple Sorting Machine by its Color
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This paper presents the basics of using a sorting system to reduce human effort and increase accuracy. This proposed system has consisted of a camera, motors, and a Raspberry Pi. This system can classify the apples as immature, mature, and ripe conditions. In this experiment, 100 apples were randomly selected by purchasing various apples from a local market. The accuracy percentage was 95%. The proposed system could be useful to reduce labor.
Abstract
This paper presents the basics of using a sorting system to reduce human effort and increase accuracy. This proposed system has consisted of a camera, motors, and a Raspberry Pi. This system can classify the apples as immature, mature, and ripe conditions. In this experiment, 100 apples were randomly selected by purchasing various apples from a local market. The accuracy percentage was 95%. The proposed system could be useful to reduce labor.
참고문헌 (5)
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- H. Patel, "IOT color based object sorting machine", International Journal of Applied Engineering Research, 13(10), pp.5~ (2018)
- S. W. Sidehabi, "The development of machine vision system for sorting passion fruit using Multi-Class Support Vector Machine", Journal of Engineering Science and Technology Review, 11(5), pp.178~184 (2018)
- S. More, "Robotic jaw for object sorting using raspberry pi", 21(2), pp.1~5 (2019)
- B. Hdioud, "Detecting and shadows in the HSV color space using dynamic thresholds", Bulletin of Electrical Engineering and Informatics, 7(1), pp.70~79 (2018)