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http://hdl.handle.net/10553/46034
| 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%. | 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 |
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