Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Maknun, Syukron"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • No Thumbnail Available
    Item
    AUTOMATIC RECOGNITION FOR TOMATOES BASED ON COMPUTER VISION ALGORITHM
    (Solid State Technology Volume: 63 Issue: 4, 2020) Maknun, Syukron; Prastyo, Rizky; Aprilio, Ronny; Gunaevi, Cevi; Wibowo, Ari Purno Wahyu
    The 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.

PTI copyright © 2002-2026

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback