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Dede Wandi
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Computer Science & IT Mathematics

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Deteksi Kelayuan Pada Bunga Mawar dengan Metode Transformasi Ruang Warna HSI Dan HSV Dede Wandi; Fauziah Fauziah; Nur Hayati
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 5, No 3 (2021)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (848.265 KB) | DOI: 10.30998/string.v5i3.8464

Abstract

The rose is a plant from the genus Rosa which has more than 100 species with various colors. In the process of selecting roses, you will find roses that are still fresh and wilted. With that, we can detect the wilting of the rose by applying the HSI and HSV methods to image processing applications, the data collection process, namely by making data preparations on the Kaggle dataset, then classifying and training the data using the HSI and HSV methods. Based on the classification results of a total of 820 images of rose images, a total of 757 images were tested using HSI and HSV. The values obtained were Range at HSI, H = 0–0.5, S = 0–1, and I = 0.5372549–1 in the Fresh category, while the category HSI wilt, H = 0–0.5, S = 0-1, I = 0.5620915–1. The HSV range values are in the Fresh category H = 0–0.5, S = 0-1, V = 0-1, and the Wilt category H = 0-0.5, S = 0-1, V = 0-1. Furthermore, the success rate for testing roses with HSI reached 92.3% where the data read correctly 757 and read incorrectly 63 out of 820 sample data of roses, while testing on HSV the success rate reached 93.2% where the data read correctly 765 and read incorrectly 55 out of 820 rose flower sample data. Based on the above results, detection of wilting roses using the HSV color space transformation method is the best in data testing.
Co-Authors Fauziah Fauziah Nur Hayati