Research Article
BibTex RIS Cite

Determination of Effective and Specific Physical Features of Rice Varieties by Computer Vision In Exterior Quality Inspection

Year 2021, Volume: 35 Issue: 3, 229 - 243, 25.12.2021

Abstract

In this study, feature extraction processes were performed based on the image processing techniques using morphological, shape and color features for five different rice varieties of the same brand. A total of 75 thousand pieces of rice grain were obtained, including 15 thousand pieces of each variety of rice. Preprocessing operations were applied to the images and made available for feature extraction. A total of 106 features were inferred from the images; 12 morphological features and 4 shape features obtained using morphological features and 90 color features obtained from five different color spaces (RGB, HSV, L*a*b*, YCbCr, XYZ). In addition, for the 106 features obtained, features were selected by ANOVA, X2 and Gain Ratio tests and useful features were determined. In all tests, out of 106 features, the 5 most effective and specific features were obtained roundness, compactness, shape factor 3, aspect ratio and eccentricity. The color features were listed in different order following these features.

There are 0 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering
Journal Section Research Article
Authors

İlkay Çınar This is me

Murat Köklü This is me

Publication Date December 25, 2021
Submission Date October 14, 2021
Published in Issue Year 2021 Volume: 35 Issue: 3

Cite

EndNote Çınar İ, Köklü M (December 1, 2021) Determination of Effective and Specific Physical Features of Rice Varieties by Computer Vision In Exterior Quality Inspection. Selcuk Journal of Agriculture and Food Sciences 35 3 229–243.

Selcuk Agricultural and Food Sciences is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).