Study on grading of betel nuts by computer vision

Authors

XU Yueming, School of Biological Engineering, Wuhu Vocational Technical College, Wuhu, Anhui 241003, China; College of Environmental Science and Engineering, Anhui Normal University, Wuhu, Anhui 241002, China
CAI Jianrong, School of Food and Biological Engineering, Jiangsu University, Jiangsu, Zhenjiang 212013, China
GONG Yinghui, School of Food and Biological Engineering, Jiangsu University, Jiangsu, Zhenjiang 212013, China

Abstract

Current technologies for grading betel nuts remain rudimentary and heavily rely on manual inspection, which results in no assurance over grading quality. This paper describes a betel nut grading method based on the computer vision technology, which comprises image capture and pre-processing to collect characteristics such as color, shape, and texture. It is observed that combining both color and shape characteristics leads to satisfactory grading results. This method can reach a recognition rate over 90.38% following principle components analysis (PCA) and a support vector machine (SVM) algorithm.

Publication Date

8-28-2016

First Page

91

Last Page

94,102

DOI

10.13652/j.issn.1003-5788.2016.08.022

Recommended Citation

Yueming, XU; Jianrong, CAI; and Yinghui, GONG (2016) "Study on grading of betel nuts by computer vision," Food and Machinery: Vol. 32: Iss. 8, Article 22.
DOI: 10.13652/j.issn.1003-5788.2016.08.022
Available at: https://www.ifoodmm.cn/journal/vol32/iss8/22

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