Machine Learning-based Whitefly Feature Identification and Counting

被引：1

作者：

Yao, Kai-Chao ^{[1
]}

Fu, Shih-Feng ^{[1
]}

Huang, Wei-Tzer ^{[1
]}

Wu, Cheng-Chun ^{[1
]}

机构：

[1] Natl Changhua Univ Educ, Dept Ind Educ & Technol, 2 Shi Da Rd, Changhua, Taiwan

来源：

JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY | 2022年 / 66卷 / 01期

关键词：

Learning algorithms - Computer programming languages - Open source software - Graphical user interfaces - Machine learning - Application programs - Digital storage - Image recognition;

D O I：

10.2352/J.ImagingSci.Technol.2022.66.1.010401

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

This article uses LabVIEW, a software program to develop a whitefly feature identification and counting technology, and machine learning algorithms for whitefly monitoring, identification, and counting applications. In addition, a high-magnification CCD camera is used for on-demand image photography, and then the functional programs of the VI library of LabVIEW NI-DAQ and LabVIEW NI Vision Development Module are used to develop image recognition functions. The grayscale-value pyramid-matching algorithm is used for image conversion and recognition in the machine learning mode. The built graphical user interface and device hardware provide convenient and effective whitefly feature identification and sample counting. This monitoring technology exhibits features such as remote monitoring, counting, data storage, and statistical analysis. & xe00d;c 2022 Society for Imaging Science and Technology.

引用

页数：9

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