Luis J. Blaanco, C. Travieso-González, José M. Quinteiro, P. V. Hernández, M. Dutta, Anushikha Singh
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引用次数: 6
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%.
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