Abstract
This paper proposes a method to detect gray spots on tea leaves using computer vision and image processing algorithms such as collecting input images from receiving equipment, removing tea leaves from the background, delineating areas of signs of disease, creating contrast. Also, in order to establish the network training parameters, a Neural of Multi-Layer Perceptron (MLP) is going to be built with extracted identifying features on the gray spots tea leaves. When the network and training the data set have been established, they will be used in the identification process and conclusions for the subject to be tested for gray spots. The identification process after many tests has achieved results with an accuracy of 90.0%.
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Binh, P.T., Nhung, T.C., Du, D.H. (2020). Detection and Diagnosis Gray Spots on Tea Leaves Using Computer Vision and Multi-layer Perceptron. In: Sattler, KU., Nguyen, D., Vu, N., Tien Long, B., Puta, H. (eds) Advances in Engineering Research and Application. ICERA 2019. Lecture Notes in Networks and Systems, vol 104. Springer, Cham. https://doi.org/10.1007/978-3-030-37497-6_27
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DOI: https://doi.org/10.1007/978-3-030-37497-6_27
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