Semi-Automated Counting of Arbuscular Mycorrhizal Fungi Spores Using Artificial Neural Network

被引：5

作者：

Melo, C. A. O. ^{[1
]}

Lopes, J. G. ^{[2
]}

Andrade, A. O. ^{[2
]}

Trindade, R. M. P. ^{[2
]}

Magalhaes, R. S. ^{[3
]}

机构：

[1] Univ Fed Bahia, Salvador, BA, Brazil

[2] Univ Estadual Sudoeste Bahia, Vitoria Da Conquista, BA, Brazil

[3] Univ Fed Sul Bahia, Itabuna, BA, Brazil

来源：

IEEE LATIN AMERICA TRANSACTIONS | 2017年 / 15卷 / 08期

关键词：

Mycorrhizal Fungi Spores; Semi-Automated Counting; Artificial Neural Networks; Fuzzy Morphology; Image Process; CLASSIFICATION; DIVERSITY;

D O I：

10.1109/TLA.2017.7994807

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Arbuscular Mycorrhizae (AM) are mutualistic associations between Arbuscular Mycorrhizal Fungi (AMF) and the roots of most plant species. The AMF spores originate filaments called hyphae that contribute to the absorption of water and nutrients, especially phosphorus. This paper presents a system that makes automatic counting of those fungi spores in slide images possible. The system facilitate and accelerate the task for specialists, since nowadays they still use manual counting. We built a database of spore images, and processed each of them through an artificial neural network to classify patterns automatically. We compared the results of our counting model based in Perceptron Artificial Neural Network with those of the Fuzzy Morphology method, using the same database. The agreement of the proposed counting model with the manual counting have been better than that of Fuzzy Morphology.

引用

页码：1566 / 1573

页数：8

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