Identifikasi Jenis Buah Tomat Berdasarkan Analisa Ekstraksi Ciri dengan menggunakan Segmentasi K-Means Clustering

Wahyu Saptha Negoro(1*), Asbon Hendra Azhar(2), Ratih Adinda Destari(3),

(1) Universitas Potensi Utama, Indonesia
(2) Universitas Potensi Utama, Indonesia
(3) Universitas Potensi Utama, Indonesia
(*) Corresponding Author

Abstract


Research on medical image processing has been widely conducted by developing various methods of image processing. The research was conducted with the aim of being able to identify images based on characteristics and segmented to determine the type of image. Identification of tomato images that have green and red types by carrying out several stages of segmentation in the form of K-Means Clustering and the value of the extraction of shape and texture features can facilitate identification. Image enhancement aims to improve image quality, so that it is easier to interpret to analyze images objectively. The tomato images used in this study were 10 images, including 5 green tomato images and 5 red tomato images. The results obtained from identification based on feature extraction and K-Means Clustering segmentation have an accuracy of 90%. Based on this study, it can be a reference in identifying tomatoes more accurately and efficiently.

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References


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DOI: https://doi.org/10.30645/kesatria.v6i2.597

DOI (PDF): https://doi.org/10.30645/kesatria.v6i2.597.g592

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