Crack Identification on the Fresh Chilli (Capsicum) Fruit Destemmed System

نویسندگان

چکیده

Destemming fresh chilli fruit (Capsicum) in large productivity is necessary, especially the Mekong Delta region. Several studies have been done to solve this problem with high applicability, but a certain percentage of output consisted cracked fruits, thus reducing quality system. The manual sorting results costs and low quality, so it necessary that automatic grading performed after destemming. This research focused on developing method identify classify fruits caused by destemming process. convolution neural network (CNN) model was built trained cracks; then, appropriate control signals were sent actuator for classification. Image processing operations are supported OpenCV library, while TensorFlow data structure used as database Keras application programming interface supports construction training models. Experiments carried out both static working conditions, which, respectively, achieved an accurate identification rate 97 95.3%. In addition, success 93% found even when body wrinkled due drying storage time at 120 hours. Practical demonstrate reliability useful acceptable.

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ژورنال

عنوان ژورنال: Journal of Sensors

سال: 2021

ISSN: ['1687-725X', '1687-7268']

DOI: https://doi.org/10.1155/2021/8838247