AUTOMATIC RECOGNITION FOR TOMATOES BASED ON COMPUTER VISION ALGORITHM

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dc.contributor.authorMaknun, Syukron
dc.contributor.authorPrastyo, Rizky
dc.contributor.authorAprilio, Ronny
dc.contributor.authorGunaevi, Cevi
dc.contributor.authorWibowo, Ari Purno Wahyu
dc.date.accessioned2021-02-20T15:54:11Z
dc.date.available2021-02-20T15:54:11Z
dc.date.issued2020
dc.description.abstractThe lack of use of computer vision technology to detect ripeness in sorting tomatoes has made farmers still use conventional methods, namely sorting based on direct visual observation of the fruit to be sorted. The disadvantage of categorizing it visually is direct which is very subjective, so it is inconsistent with the sorting process for the level of ripeness of the tomatoes. Therefore, sorting tomatoes utilizing technological sophistication needs to be done. The construction of this system uses a Radial Basic Neural Network Algorithm with RGB value parameters, and the mean, entropy, and variance values using a Gabor filter in the form of GUI (Graphical User Interface) connected to a webcam equipped with a servo which plays an important role as a tomato fruit sorting mechanism. This is expected to be able to help farmers in the sorting process for ripe tomatoes. In this experiment, a sorting system was carried out to detect maturity based on color changes in objects, in the experiment an accuracy was obtained that the computer vision algorithm was able to recognize and sort tomatoes by up to 90% using random sample data.en_US
dc.identifier.issn0038-111X
dc.identifier.urihttp://repository.widyatama.ac.id/xmlui/handle/123456789/12715
dc.language.isoenen_US
dc.publisherSolid State Technology Volume: 63 Issue: 4en_US
dc.subjectRadial Basic Neural Network Algorithmen_US
dc.subjectGabor Filteren_US
dc.subjectRGBen_US
dc.titleAUTOMATIC RECOGNITION FOR TOMATOES BASED ON COMPUTER VISION ALGORITHMen_US
dc.typeArticleen_US
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