This paper proposed a grape drying machine using computer vision and Multi-layer Perceptron (MLP) method. Computer vision is for taking grapes’ image on conveyor, whereas MLP is for controlling grape drying machine and classifying its output. To evaluate the proposed, a kind of grapes are put on conveyor of the machine and their images are taken every two min. Some parameters of MLP to control the drying machine includes dried grape, temperature, grape area, motor position, and motion speed. Those parameters are to adjust an appropriate MLP’s output, including motion control and heater control. Two different temperatures are employed on the machine, including 60 and 75°C. The results showed that the grape could be dried with similar area 3800 pixel at the 770th min using temperature 60°C and at the 410th min using temperature 75°C. Comparing between them, the similar ratio could also be achieved at 0.64 with different time 360 min. Indeed, the temperature setting at 75°C resulted faster drying performance.


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    Title :

    Grape Drying Process Using Machine Vision Based on Multilayer Perceptron Networks


    Contributors:

    Publication date :

    2020-12-01


    Remarks:

    doi:10.17509/ijost.v5i3.24991
    Indonesian Journal of Science and Technology; Vol 5, No 3 (2020): IJOST: VOLUME 5, ISSUE 3, 2020; 382-394 ; 2527-8045 ; 2528-1410 ; 10.17509/ijost.v5i3



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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