Using the Support Vector Machine method with the HOG feature for classification of orchid types

Authors

  • Sri Andayani Fakultas Sains dan Teknologi, Universitas Katolik Musi Charitas
  • Leni Kusneti Fakultas Sains dan Teknologi, Universitas Katolik Musi Charitas

DOI:

https://doi.org/10.24246/aiti.v21i1.82-95

Keywords:

orchids, leaf morphology, species, SVM, HOG

Abstract

Orchids are the most species-rich flowering plants, with approximately 750 genera and 43,000 types of orchids in the world, of which about 5,000 species have been recorded in several provinces in Indonesia. Orchids have beautiful flowers with attractive colors, making them ornamental plants that many people like. From plant morphology, orchid plants can be differentiated based on the morphology of flowers, leaves, fruit, stems, and roots. The leaves of orchid plants have their characteristics for each type of orchid, such as long, round, or lanceolate. All orchids have veins that run parallel to their leaves. The individual shapes of orchid leaves can be classified using a Support Vector Machine (SVM) and Histogram of Gradient (HOG). In this research, five types of orchids that are popular among orchid lovers were used, namely Dendrobium, Cattleya, Oncidium, Phalaenopsis, and Vanda orchids, which were taken from public data. The accuracy of this method in classifying orchid species based on leaf morphology can be measured using a confusion matrix that measures precision, recall, and accuracy. From five tests, the Oncidium orchid had the highest average accuracy with a value of 98%, the Vanda orchid had the highest average precision of 99.80%, and the Cattleya orchid had the highest average recall of 100%.

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Published

2024-04-02

How to Cite

[1]
S. Andayani and L. Kusneti, “Using the Support Vector Machine method with the HOG feature for classification of orchid types”, AITI, vol. 21, no. 1, pp. 82–95, Apr. 2024.

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