|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
|UNESCO Clasification:||3307 Tecnología electrónica||Keywords:||Classification algorithm
Support vector machines
Discrete wavelet transforms
|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%.||URI:||http://hdl.handle.net/10553/46034||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|