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Title: A bark recognition algorithm for plant classification using a least square support vector machine
Authors: Blaanco, Luis J.
Travieso, Carlos M. 
Quinteiro, Jose M. 
Hernandez, Pablo V. 
Dutta, Malay Kishore
Singh, Anushikha
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Classification algorithm
Support vector machines
Discrete wavelet transforms
Biology computing
Pattern classification
Issue Date: 2017
Journal: 2016 Ninth International Conference On Contemporary Computing (Ic3)
Conference: 9th International Conference on Contemporary Computing, IC3 2016 
Abstract: In this paper, a bark recognition algorithm for plant classification is presented. A Least-Square Support Vector Machine (LSSVM) with image and data processing techniques is used to implement a general purpose automated classifier. Using a data base of 40 sections of photographs taken of each of the 23 species, we applied an algorithm to homogenize the illumination of the images. After applying it, we obtained a 256-elements array from the Local Binary Pattern (LBP) histogram. Each element of the array was introduced in the LSSVM for classification. The success rate of the resultant recognizer is 82.38%.
ISBN: 9781509032518
ISSN: 2572-6110
DOI: 10.1109/IC3.2016.7880233
Source: 2016 9th International Conference on Contemporary Computing, IC3 2016 (7880233)
Appears in Collections:Actas de congresos
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