Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task

Carlos Arrasco; Sofia Khlebnikov; Arturo Oncevay; Cesar Beltran Castanon

doi:10.1109/LA-CCI.2018.8625221

Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task

Carlos Arrasco, Sofia Khlebnikov, Arturo Oncevay, Cesar Beltran Castanon

Pontifical Catholic Univ. of Peru

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

3 Scopus citations

Abstract

In a computer science approach, the plant classification task focuses on the extraction of many leaf attributes, such as texture or veins, which are closely related and commonly analyzed together. Thereby, this study proposes a method to enhance the venation patterns over the leaf area, in order to improve the texture feature extraction in windows areas in the plant species identification. Regarding the experimentation, two types of texture features are contrasted, and it is performed over an own dataset with high-resolution image of 10 plant species. The obtained results demonstrate that the veins enhancing process improve the species classification task significantly for a texture descriptor based on the analysis of relation between neighboring pixels.

Original language	English
Title of host publication	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538646250
DOIs	https://doi.org/10.1109/LA-CCI.2018.8625221
State	Published - 23 Jan 2019
Event	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 - Gudalajara, Mexico Duration: 6 Nov 2018 → 9 Nov 2018

Publication series

Name	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018

Conference

Conference	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Country/Territory	Mexico
City	Gudalajara
Period	6/11/18 → 9/11/18

Keywords

Haralick's descriptors
leaf veins extraction
leaf venation enhancing
leaf-based plant classification
multi-scale fractal dimension
texture feature extraction

Access to Document

10.1109/LA-CCI.2018.8625221

Cite this

Arrasco, C., Khlebnikov, S., Oncevay, A., & Castanon, C. B. (2019). Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task. In 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 Article 8625221 (2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LA-CCI.2018.8625221

Arrasco, Carlos ; Khlebnikov, Sofia ; Oncevay, Arturo et al. / Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task. 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018. Institute of Electrical and Electronics Engineers Inc., 2019. (2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018).

@inproceedings{8f860c63fe8844b4b20a5e8229d55e30,

title = "Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task",

abstract = "In a computer science approach, the plant classification task focuses on the extraction of many leaf attributes, such as texture or veins, which are closely related and commonly analyzed together. Thereby, this study proposes a method to enhance the venation patterns over the leaf area, in order to improve the texture feature extraction in windows areas in the plant species identification. Regarding the experimentation, two types of texture features are contrasted, and it is performed over an own dataset with high-resolution image of 10 plant species. The obtained results demonstrate that the veins enhancing process improve the species classification task significantly for a texture descriptor based on the analysis of relation between neighboring pixels.",

keywords = "Haralick's descriptors, leaf veins extraction, leaf venation enhancing, leaf-based plant classification, multi-scale fractal dimension, texture feature extraction",

author = "Carlos Arrasco and Sofia Khlebnikov and Arturo Oncevay and Castanon, {Cesar Beltran}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 ; Conference date: 06-11-2018 Through 09-11-2018",

year = "2019",

month = jan,

day = "23",

doi = "10.1109/LA-CCI.2018.8625221",

language = "English",

series = "2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018",

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Arrasco, C, Khlebnikov, S, Oncevay, A & Castanon, CB 2019, Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task. in 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018., 8625221, 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, Gudalajara, Mexico, 6/11/18. https://doi.org/10.1109/LA-CCI.2018.8625221

Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task. / Arrasco, Carlos; Khlebnikov, Sofia; Oncevay, Arturo et al.
2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8625221 (2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018).

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

TY - GEN

T1 - Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task

AU - Arrasco, Carlos

AU - Khlebnikov, Sofia

AU - Oncevay, Arturo

AU - Castanon, Cesar Beltran

PY - 2019/1/23

Y1 - 2019/1/23

N2 - In a computer science approach, the plant classification task focuses on the extraction of many leaf attributes, such as texture or veins, which are closely related and commonly analyzed together. Thereby, this study proposes a method to enhance the venation patterns over the leaf area, in order to improve the texture feature extraction in windows areas in the plant species identification. Regarding the experimentation, two types of texture features are contrasted, and it is performed over an own dataset with high-resolution image of 10 plant species. The obtained results demonstrate that the veins enhancing process improve the species classification task significantly for a texture descriptor based on the analysis of relation between neighboring pixels.

AB - In a computer science approach, the plant classification task focuses on the extraction of many leaf attributes, such as texture or veins, which are closely related and commonly analyzed together. Thereby, this study proposes a method to enhance the venation patterns over the leaf area, in order to improve the texture feature extraction in windows areas in the plant species identification. Regarding the experimentation, two types of texture features are contrasted, and it is performed over an own dataset with high-resolution image of 10 plant species. The obtained results demonstrate that the veins enhancing process improve the species classification task significantly for a texture descriptor based on the analysis of relation between neighboring pixels.

KW - Haralick's descriptors

KW - leaf veins extraction

KW - leaf venation enhancing

KW - leaf-based plant classification

KW - multi-scale fractal dimension

KW - texture feature extraction

UR - http://www.scopus.com/inward/record.url?scp=85062535809&partnerID=8YFLogxK

U2 - 10.1109/LA-CCI.2018.8625221

DO - 10.1109/LA-CCI.2018.8625221

M3 - Conference contribution

AN - SCOPUS:85062535809

T3 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018

BT - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018

Y2 - 6 November 2018 through 9 November 2018

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Arrasco C, Khlebnikov S, Oncevay A, Castanon CB. Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task. In 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018. Institute of Electrical and Electronics Engineers Inc. 2019. 8625221. (2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018). doi: 10.1109/LA-CCI.2018.8625221

Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task

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