Leaf recognition for plant classification based on wavelet entropy and back propagation neural network

Meng Meng Yang; Preetha Phillips; Shuihua Wang; Yudong Zhang

doi:10.1007/978-3-319-65298-6_34

Leaf recognition for plant classification based on wavelet entropy and back propagation neural network

Meng Meng Yang, Preetha Phillips, Shuihua Wang, Yudong Zhang^*

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

4 Citations (Scopus)

Abstract

In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings
Editors	Honghai Liu, YongAn Huang, Hao Wu, Zhouping Yin
Publisher	Springer Verlag
Pages	367-376
Number of pages	10
ISBN (Print)	9783319652979
DOIs	https://doi.org/10.1007/978-3-319-65298-6_34
Publication status	Published - 2017
Externally published	Yes
Event	10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 - Wuhan, China Duration: 16 Aug 2017 → 18 Aug 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10464 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Intelligent Robotics and Applications, ICIRA 2017
Country/Territory	China
City	Wuhan
Period	16/08/17 → 18/08/17

Keywords

Back-Propagation
Classification
Feature extraction
K-fold cross-validation
Pattern recognition

Access to Document

10.1007/978-3-319-65298-6_34

Cite this

Yang, M. M., Phillips, P., Wang, S., & Zhang, Y. (2017). Leaf recognition for plant classification based on wavelet entropy and back propagation neural network. In H. Liu, Y. Huang, H. Wu, & Z. Yin (Eds.), Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings (pp. 367-376). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10464 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-65298-6_34

Yang, Meng Meng ; Phillips, Preetha ; Wang, Shuihua et al. / Leaf recognition for plant classification based on wavelet entropy and back propagation neural network. Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. editor / Honghai Liu ; YongAn Huang ; Hao Wu ; Zhouping Yin. Springer Verlag, 2017. pp. 367-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4e99007753fd4dbbb3bf019cd40ee13a,

title = "Leaf recognition for plant classification based on wavelet entropy and back propagation neural network",

abstract = "In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.",

keywords = "Back-Propagation, Classification, Feature extraction, K-fold cross-validation, Pattern recognition",

author = "Yang, {Meng Meng} and Preetha Phillips and Shuihua Wang and Yudong Zhang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 ; Conference date: 16-08-2017 Through 18-08-2017",

year = "2017",

doi = "10.1007/978-3-319-65298-6_34",

language = "English",

isbn = "9783319652979",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "367--376",

editor = "Honghai Liu and YongAn Huang and Hao Wu and Zhouping Yin",

booktitle = "Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings",

}

Yang, MM, Phillips, P, Wang, S & Zhang, Y 2017, Leaf recognition for plant classification based on wavelet entropy and back propagation neural network. in H Liu, Y Huang, H Wu & Z Yin (eds), Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10464 LNAI, Springer Verlag, pp. 367-376, 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017, Wuhan, China, 16/08/17. https://doi.org/10.1007/978-3-319-65298-6_34

Leaf recognition for plant classification based on wavelet entropy and back propagation neural network. / Yang, Meng Meng; Phillips, Preetha; Wang, Shuihua et al.
Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. ed. / Honghai Liu; YongAn Huang; Hao Wu; Zhouping Yin. Springer Verlag, 2017. p. 367-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10464 LNAI).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Leaf recognition for plant classification based on wavelet entropy and back propagation neural network

AU - Yang, Meng Meng

AU - Phillips, Preetha

AU - Wang, Shuihua

AU - Zhang, Yudong

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.

AB - In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.

KW - Back-Propagation

KW - Classification

KW - Feature extraction

KW - K-fold cross-validation

KW - Pattern recognition

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DO - 10.1007/978-3-319-65298-6_34

M3 - Conference Proceeding

AN - SCOPUS:85028296576

SN - 9783319652979

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 367

EP - 376

BT - Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings

A2 - Liu, Honghai

A2 - Huang, YongAn

A2 - Wu, Hao

A2 - Yin, Zhouping

PB - Springer Verlag

T2 - 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017

Y2 - 16 August 2017 through 18 August 2017

ER -

Yang MM, Phillips P, Wang S, Zhang Y. Leaf recognition for plant classification based on wavelet entropy and back propagation neural network. In Liu H, Huang Y, Wu H, Yin Z, editors, Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. Springer Verlag. 2017. p. 367-376. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-65298-6_34

Leaf recognition for plant classification based on wavelet entropy and back propagation neural network

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