Year: 2024
Type: article
Abstract: Plants are incredibly beneficial to human survival in various ways. Leaves are part of plants widely used as medicine. They are similar in shape but have different advantages. Leaf types can only be identified by experts. This study aims to create a classification system for herbal leaves based on the Haar wavelet transform and machine learning. The study was carried out to assist ordinary people in recognizing herbal leaves. The results revealed that Haar wavelet level 1 was better suited to the leaf data. The Quadratic SVM model yielded the highest result with an accuracy of 77%, a precision of 83%, a recall of 83%, a specificity of 82%, and an F-score of 73%.
Authors: Yessi Jusman, Arif Arisandy Kusumaning Putri, Anna Nur Nazilah Chamim, Yudhi Ardiyanto
Institution: Muhammadiyah University of Yogyakarta
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6959401884
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