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akaturk Akademik ölçüm

Makale detayı · 2021

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

Dergi

Selcuk Journal of Agriculture and Food Sciences

ISSN 2458-8377

YÖKSİS OpenAlex Açık erişim · diamond JCR Q4 TR Index Atıf 31 Yüzdelik 83.5% FWCI 1.84
Yıl
2021
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • YÖKSİS dergi adı Selcuk Journal of Agriculture and Food Sciences
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

İngilizce (OpenAlex)

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. Pre-processing 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.

Konular

  • Spectroscopy and Chemometric Analyses
  • GABA and Rice Research

Birincil konu Spectroscopy and Chemometric Analyses

Yazarlar

  1. İLKAY ÇINAR SELÇUK ÜNİVERSİTESİ
  2. MURAT KÖKLÜ SELÇUK ÜNİVERSİTESİ