Classification of Corn Seed and Cob Quality Based on Texture and RGB Color Features Using Backpropagation Method - Pawening, Ratri Enggar; Zaskiya, Karina Desy; Hasanah, Syarifatul (Institute of Computer Science (IOCS), 2024)
The quality of agricultural products, such as corn, is greatly influenced by various factors, both environmental factors and agricultural engineering factors. This post-harvest quality affects product performance and is in line with consumer satisfaction, so it will greatly affect its selling price. Manual corn quality grouping requires a lot of time and effort. This study aims to develop a method for classifying corn kernel and cob quality based on digital image processing, using RGB color and texture features. The dataset consists of 150 corn kernel images divided into two quality categories, namely