Rice Quality Analysis Using Machine Learning

EasyChair Preprint 4761

Abstract

Rice is the most consuming food all over the world and the market for rice is always high. In rice manufacturing industries the market demand is always centered on quality of rice. In the evaluation of rice quality the examination of physical dimensions like length, width and thickness plays an important role. Traditional methods used for detection these factors are time consuming and imprecise as they are done manually. This paved the way for development of computerized vision in rice quality inspection. In the proposed method both image processing and machine learning techniques are clubbed to analyze and grade the quality of rice kernels with the help of Support Vector Machine (SVM) classifier in python platform.

Keyphrases: Python, Rice quality, SVM, image processing, machine learning

@booklet{EasyChair:4761,
  author    = {Pavankumar Annadasu and K Jaisharma},
  title     = {Rice Quality Analysis Using Machine Learning},
  howpublished = {EasyChair Preprint 4761},
  year      = {EasyChair, 2020}}