期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2020
卷号：18
期号：4
页码：1897-1903
DOI：10.12928/telkomnika.v18i4.14069
出版社：Universitas Ahmad Dahlan
摘要：Rice is a primary source of food consumed by almost half of world population. Rice quality mainly depends on the purity of the rice seed. In order to ensure the purity of rice variety, the recognition process is an essential stage. In this paper, we firstly propose to use histogram of oriented gradient (HOG) descriptor to characterize rice seed images. Since the size of image is totally random and the features extracted by HOG can not be used directly by classifier due to the different dimensions. We apply several imputation methods to fill the missing data for HOG descriptor. The experiment is applied on the VNRICE benchmark dataset to evaluate the proposed approach.
关键词：HOG descriptor; KNN imputation; linear interpolation; missing value imputation; rice seed image classification; zero imputation;
