Title
Leaf Venation Enhancing for Texture Feature Extraction in a Plant Classification Task
Date Issued
23 January 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
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.
Language
English
OCDE Knowledge area
Ciencias de la computación
Ciencias de las plantas, Botánica
Subjects
Scopus EID
2-s2.0-85062535809
ISBN
9781538646250
Resource of which it is part
2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
ISBN of the container
978-153864625-0
Conference
2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Sponsor(s)
For this study, the authors acknowledge the support of the ”Programa Nacional de Innovacion para la Competitividad y Productividad”, INNOVATE Peru, under the contract 183-FINCyT-IA-2013.
Sources of information:
Directorio de Producción Científica
Scopus