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Recognition system for wooded species of Canary Laurisilva from its contour using kernel of Fisher

机译:采用渔业内核从其轮廓的金丝雀Laurisilva识别系统

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In this work it has been developed a novel system of automatic recognition for trees leaves, based on a hybrid classification method by means of a Support Vector Machine (SVM), using the Fisher kernel, and calculated from a Hidden Markov Model (HMM). An angle sequence has been used as an element of parameterization, extracted from the leaves contour, making such sequence invariable by rotation, movements and size. The application of these algorithms has been focused on the implementation of a recogniser of leaves of endemic trees from the Canary Islands, in particular, 16 different species of Canary Laurisilva. Obtained successful rates have been higher than 99.9%, according to the number of employed leaves in the training process.
机译:在这项工作中,它已经开发了一种新颖的自动识别系统,用于树木离开,基于通过支持向量机(SVM),使用Fisher内核,并从隐藏的马尔可夫模型(HMM)计算。角度序列已被用作参数化的元素,从叶子轮廓中提取,通过旋转,移动和尺寸使得诸如序列不变。这些算法的应用已经专注于从加那利群岛的流行树叶叶片的识别者的实施,特别是16种不同种类的金丝雀桂氏菌。根据培训过程中使用的叶片数量,获得的成功率高于99.9%。

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