Perancangan Sistem Deteksi Warna Real-Time Menggunakan Metode Gaussian Blur Dan Ruang Warna HSV
Keywords:
Deteksi Warna, Pengolahan Real-Time, OpenCV, Ruang Warna HSV, Pengolahan CitraAbstract
Color detection is a crucial process in recognizing objects based on their color characteristics in an image. This research designs a real-time color detection system using OpenCV and HSV color space to aid individuals in easily identifying colors. The system employs image processing techniques such as Gaussian blur and morphological operations to enhance detection accuracy. Designed to detect and recognize multiple colors including red, green, blue, yellow, orange, purple, brown, black, white, and gray, the system displays detection results by drawing bounding boxes around detected objects and providing clear and readable color labels. Implemented by accessing the camera directly, processing each frame in real-time, and displaying detection results on-screen, the system demonstrates satisfactory performance in good lighting conditions and is capable of detecting objects of various sizes, thereby providing significant visual assistance in color identification and differentiation in the surrounding environment.
References
Goenawan, A. D., Rachman, M. B. A., & Pulungan, M. P. (2022). Identifikasi Warna Pada Objek Citra Digital Secara Real Time Menggunakan Pengolahan Model Warna HSV. Jurnal Teknik Informatika Dan Elektro, 4(1), 68–74. https://doi.org/10.55542/jurtie.v4i1.430
Nugroho, A., Fauzi, A., Sunarko, B., Wibawanto, H., & Iksan, N. (2022). Simplifikasi Model Cv Teregularisasi Berpadu Operasi. Jurnal Informatika Polinema, 8(2), 49–56. http://jip.polinema.ac.id/ojs3/index.php/jip/article/view/913
Panggabean, A. K., Ayu, N., & Syahfaridzah, A. (2021). Mendeteksi Objek Berdasarkan Warna Dengan Segmentasi Warna Hsv Menggunakan Aplikasi Matlab. METHOMIKA Jurnal Manajemen Informatika Dan Komputerisasi Akuntansi, 4(2), 94–97. https://doi.org/10.46880/jmika.vol4no2.pp94-97
Rabbani, H. A., Rahman, M. A., & Rahayudi, B. (2021). Perbandingan Ruang Warna RGB dan HSV dalam Klasifikasi Kematangan Biji Kopi. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 5(6), 2243–2248. http://j-ptiik.ub.ac.id
Rosyani, P., Amalia, R., & Ikasari, I. H. (2021). Deteksi Objek dengan Model Warna Ycbcr dan Similiarity Distance. Jurnal Sistem Dan Teknologi Informasi (Justin), 9(2), 98. https://doi.org/10.26418/justin.v9i2.44230
Rosyani, P., Fauziah, E., Sadewo, F. B., & Putra, H. M. (2024). Penerapan Image Processing Menggunakan OpenCV dan Python untuk Memperhalus Gambar Melalui Smoothing Image dengan Metode Gaussian Blur. 13(2), 1–7.
Rosyani, P., Tingkat, K., Buah, K., Seknun, A. Z., Kusuma, A., Sabrina, A., Dwi, A., & Putri, C. (2023). Tomat Dengan Variasi Model Warna. 1(2), 203–210.
Sari, D. A. L., Mulyadi, A., Pratama, A., & ... (2020). Deteksi Objek Berwarna Real Time Berdasarkan Visualisasi Webcam. Journal …, 02(01), 21–24. https://ejournal.unibabwi.ac.id/index.php/Zetroem/article/view/1336
Utami. (2023). Deteksi Objek Kualitas Daun Sawi Menggunakan Metode HSV Color dan Color Blob. JUSIBI (Jurnal Sistem Informasi Dan Bisnis), 5(2), 85–93. https://doi.org/10.54650/jusibi.v5i2.518
Yasir, A., Satria, W., & Yuanda, P. (2023). Digital Image Processing Metode Median Filtering Dan Morfologi Opening Dalam Reduksi Noise Citra. Warta Dharmawangsa, 17(4), 1687–1701. https://doi.org/10.46576/wdw.v17i4.3821