PJB-2023-503
AUTOMATED COLOR EVALUATION OF BENENG LEAVES USING IMAGEJ MACRO TOOL AND K-MEAN ALGORITHM FOR QUALITY ASSESSMENT
Pepi Nur Susilawati
Abstract
This study presents an automated image analysis approach to quantify and cluster the color of beneng leaves (Xanthosoma undipes K. Koch), a wild taro cultivated in Indonesia for its dried and chopped leaves. A color macro tool was developed in ImageJ software, enabling the extraction of quantitative color data from RGB, Lab, and HSB color spaces. The analysis revealed that cutting and destruction treatments influenced leaf senescence, resulting in higher green, blue, and b* values. Furthermore, clustering analysis using the K-Means algorithm categorized the leaves into three clusters based on yellow color intensity. These findings contribute to the evaluation of beneng leaf quality and can support the establishment of quality standards and cultivation strategies.
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