Next Article in Journal
Coastal Areas Division and Coverage with Multiple UAVs for Remote Sensing
Next Article in Special Issue
A Quadrilateral Geometry Classification Method and Device for Femtocell Positioning Networks
Previous Article in Journal
Estimation of Antenna Pose in the Earth Frame Using Camera and IMU Data from Mobile Phones
Previous Article in Special Issue
Liquid Temperature Measurements Using Two Different Tunable Hollow Prisms
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(4), 809;

A Novel Method of Identifying Paddy Seed Varieties

Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Tai-Chung 402, Taiwan
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 11 February 2017 / Revised: 1 April 2017 / Accepted: 5 April 2017 / Published: 9 April 2017
(This article belongs to the Special Issue Innovative Sensing Control Scheme for Advanced Materials)
Full-Text   |   PDF [5420 KB, uploaded 9 April 2017]   |  


This paper presents a novel method for identifying three varieties (Taikong 9, Tainan 11, and Taikong 14) of foundation paddy seeds. Taikong 9, Tainan 11, and Taikong 14 paddy seeds are indistinguishable by inspectors during seed purity inspections. The proposed method uses image segmentation and a key point identification algorithm that can segment paddy seed images and extract seed features. A back propagation neural network was used to establish a classifier based on seven features that could classify the three paddy seed varieties. The classification accuracies of the resultant classifier for varieties Taikong 9, Tainan 11, and Taikong 14 were 92.68%, 97.35% and 96.57%, respectively. The experimental results indicated that the three paddy seeds can be differentiated efficiently using the developed system. View Full-Text
Keywords: paddy seeds; image processing; identification paddy seeds; image processing; identification

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Huang, K.-Y.; Chien, M.-C. A Novel Method of Identifying Paddy Seed Varieties. Sensors 2017, 17, 809.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top