Automated estimation of grape ripeness

  • Kaveri Kangune
  • Dr. Vrushali Kulkarni
  • Prof. Pranali Kosamkar

Abstract

India is worldwide well known for exporting
fruits, having immense importance in the world. Global
food security is necessary for not only durable
production of fruits but also for remarkable reduction in
pre and post- harvest waste. Harvesting fruits and
detecting ripeness of fruits by human is an expensive,
laborious and time consuming task. For this reason,
there is need for an automated ripeness estimation
system in the last decade. Fruit ripeness estimation is
major task that influence its quality and later its
marketing. Researchers have started targeting towards
for the study of ripeness estimation using methods in
image processing and machine learning to automatic
classification of ripeness of fruit accurately, quickly and
non-destructively. Traditional methods for fruit ripeness
estimation considered fruits such as orange, apple,
tomato, banana, papaya and etc. which is single fruit. By
taking into account increasing productivity of grapes
and bunch of berries in grapes need to focus on
estimation of ripeness of grapes fruit. We have reviewed
various studies in this domain and believe this is a
primary effort in summarizing the highlights of
researches done. This will give direction for fellow
researchers.
 

Keywords: Ripeness estimation, image processing, Deep Learning, Convolution Neural Networks

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How to Cite
Kangune, K., Kulkarni, D. V., & Kosamkar, P. P. (2019). Automated estimation of grape ripeness. Asian Journal For Convergence In Technology (AJCT). Retrieved from http://www.asianssr.org/index.php/ajct/article/view/792
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