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Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
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Sensors and Materials, Volume 32, Number 11(2) (2020)
Copyright(C) MYU K.K.
pp. 3647-3657
S&M2365 Research Paper of Special Issue
Published: November 18, 2020

Development of a Novel Autoinspection System for Paddy Seed Early-germination Performance [PDF]

An-Qin Xu, Shi-Jie Luo, Feng-Yi Liao, I-Cheng Chen, Mao-Chien Chien, and Kuo-Yi Huang

(Received July 22, 2020; Accepted October 11, 2020)

Keywords: paddy seedlings, machine vision, autoinspection

We present a novel vision machine for autoinspecting paddy seed early germination. The system comprises an inlet–outlet mechanism, machine vision hardware and software, and a control system for inspecting paddy seed early germination. Differences in color are used to segment the structure of germinating seedlings. A thinning operator is employed to extract the skeleton of the root system, and the skeleton pruning method is used to remove branched roots and extract taproots. Features such as the length and width of the taproot and the length and curvature of the seed axis are provided as the input neurons of neural networks to classify seed germination as “normal” or “abnormal”. The inspection accuracy was found to be 86.09%. The experimental results indicated that early-germinating paddy seeds can be inspected efficiently by using the developed system.

Corresponding author: Kuo-Yi Huang

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Cite this article
An-Qin Xu, Shi-Jie Luo, Feng-Yi Liao, I-Cheng Chen, Mao-Chien Chien, and Kuo-Yi Huang, Development of a Novel Autoinspection System for Paddy Seed Early-germination Performance, Sens. Mater., Vol. 32, No. 11, 2020, p. 3647-3657.

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