The Open Cybernetics & Systemics Journal


ISSN: 1874-110X ― Volume 12, 2018

Seed Identification of Gramineous Grass Using Local Similarity Pattern and Linear Discriminant Analysis

Tong Chen1, Xin Pan1, *, Yubao Ma2, Weihong Yan2, Guifang Wu3, Zhihong Yu3
1 College of Computer and Information Engineering, Inner Mongolia Agricultural University, Huhhot, Inner Mongolia 010018, P.R. China
2 Grassland Research Institute of Chinese Academy of Agricultural Sciences, Huhhot, Inner Mongolia 010010, P.R. China
3 College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Huhhot, Inner Mongolia 010018, P.R. China



Grass Seed Identification Using LSP and LDA.


Forage plays an important role in grassland in providing food for the livestock and keeping balance for the ecological system. Automated identification of fora-ge is an important task to improve the grassland management. Forage seed is the vital organ with relatively stable characteristics. Different from the relatively obvious varia-tions among the weeds, forage seeds are very similar in color, shape, size and texture. Especially, the resemblance of some seeds from different families makes the identification more difficult.


In this paper, we proposed a seed identification approach based on local similarity pattern and linear discriminant analysis for gramineous grass, one of the main forge categories of the grassland, for a better identification performance.


The textural features derived from local similarity pattern and histogram statistics were input into linear discriminant analysis classifier, in which the former can extract more specific textures robust to noise and rotation variance, and the latter was more discriminative with classification information.


Experiments conducted on similar gramineous grass seeds of 12 species demonstrated the effectiveness of the algorithm, yielding an identification accuracy of 91.07%.


Therefore, local similarity pattern and linear discriminant analysis classifier can well solve the identification problems of similar gramineous grass seeds.

Keywords: Seed identification, Local similarity pattern, Textural features, Linear discriminant analysis, Gramineous grass.

Article Information

Identifiers and Pagination:

Year: 2017
Volume: 11
First Page: 108
Last Page: 118
Publisher Id: TOCSJ-11-108
DOI: 10.2174/1874110X01711010108

Article History:

Received Date: 11/01/2017
Revision Received Date: 09/03/2017
Acceptance Date: 12/04/2017
Electronic publication date: 30/05/2017
Collection year: 2017

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© 2017 Chen et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: ( This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the College of Computer and Information Engineering, Inner Mongolia Agricultural University, Huhhot, Inner Mongolia 010018, P.R. China; Tel: 86-15847129078; E-mails:,


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