Optimization of Gray Level Co-occurrence Matrix (GLCM) Texture Feature Parameters in Determining Rice Seed Quality

Optimization of Gray Level Co-occurrence Matrix (GLCM) Texture Feature Parameters in Determining Rice Seed Quality

Rice seed quality assessment is a critical measure in promoting agricultural productivity, as high-quality seeds directly influence crop yield and resilience. One of method for evaluating seed quality is texture analysis, which leverages the Gray Level Co-occurrence Matrix (GLCM) to extract meaning...

Full description

Saved in:
Bibliographic Details
Main Authors: Aji Setiawan, Adam Arif Budiman
Format: Article
Language:English
Published: Politeknik Elektronika Negeri Surabaya 2025-06-01
Series:Emitter: International Journal of Engineering Technology
Subjects:
GLCM
rice seed quality
texture parameters
feature optimization
texture analysis
Online Access:https://emitter.pens.ac.id/index.php/emitter/article/view/928
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items