Classification of Immature and Mature Coffee Beans Using Texture Features and Medium K-Nearest Neighbor  

作　　者：Edwin R.Arboleda 

机构地区：[1]Department of Computer and Electronics Engineering,College of Engineering and Information Technology,Cavite State University,Indang,Cavite,Philippines

出　　处：《Journal of Artificial Intelligence and Technology》2023年第3期114-118,共5页人工智能技术学报（英文）

摘　　要：In this study,texture features namely entropy,contrast,energy,and homogeneity are extracted from mature and immature coffee beans using image processing,and the values are inputted into MATLAB’s Classification Learner App for discrimination.Among the 23 machine-learning algorithms,the best performance was achieved by medium K-nearest neighbor which has 97%accuracy and 0.14574 seconds in speed.When compared with previous studies that used RGB and HSV color features to differentiate mature and immature coffee beans,it can be concluded that texture features are far superior in distinguishing the two coffee bean groups.

关 键 词：COFFEE energy ENTROPY HOMOGENEITY machine learning TEXTURE 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]