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All Journal JSAI (Journal Scientific and Applied Informatics)
Inge Handriani
Fakultas Ilmu Komputer, Universitas Mercu Buana
Computer Science & IT

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Application of Random Contrast and Brightness Range Methods on Phytomedicine Leaf Image Dataset Mariana Purba; Vina Ayumi; Sarwati Rahayu; Umniy Salamah; Inge Handriani; Ida Farida
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8766

Abstract

This study aimed to enhance the performance of deep learning models in detecting and classifying medicinal plant leaf images by applying two data augmentation techniques, namely Random Contrast Augmentation (RCA) and Brightness Range Augmentation (BRA). The RCA technique randomly adjusted the contrast of images by calculating the pixel average and modifying each pixel value based on a contrast factor, thereby increasing the variation in image lighting. Meanwhile, BRA randomly altered the brightness of the images to simulate varying lighting conditions. The research process began with the collection of medicinal plant leaf image datasets, which were then divided into three parts: training data, validation data, and testing data. The dataset was then pre-processed to prepare the images before applying the augmentation. Augmentation techniques were employed to enrich the dataset by generating modified copies of images using RCA and BRA techniques. The application of both augmentation techniques resulted in a training dataset of 2,400 images, 300 validation images, and 300 testing images.
Co-Authors Ida Farida Mariana Purba Sarwati Rahayu Umniy Salamah Vina Ayumi