Chroma Key untuk Mengubah Warna Pakaian dengan HSV dan Morfologi pada Citra Digital

 (*)Sayuti Rahman Mail (Universitas Harapan Medan, Medan, Indonesia)
 M F Verri Anggriawan (Universitas Harapan Medan, Medan, Indonesia)
 Rosyidah Siregar (Universitas Harapan Medan, Medan, Indonesia)
 Siti Sundari (Universitas Harapan Medan, Medan, Indonesia)
 Kharunnisa Kharunnisa (Universitas Harapan Medan, Medan, Indonesia)
 Muhammad Zen (Universitas Pembangunan Panca Budi, Medan, Indonesia)

(*) Corresponding Author

Abstract

Currently, Indonesia is still under the influence of the COVID-19 virus. Indonesian people buy necessities of life on the online market. Clothing is a daily necessity that people often buy online. This has an impact on increasing online clothing sales, but not all clothes are according to the tastes of buyers. Therefore we need an application that is used to speed up changing the color of clothes according to the needs of buyers. The chroma key application that is used to change the color of the clothing image uses the HSV and morphology classification methods. Edge detection and median filters are used to improve the quality of color shift results with HSV. This application is built using MatLab 2015a programming. The test results show that the HSV classification method is better at changing the color of the clothing image than the morphological method. The HSV classification method was successful in changing the color of clothes well with a 100% success rate. While the morphological method succeeded in changing the color of the clothes with a success rate of 60%.

Keywords


Chroma Key; Image Processing; Color of Clothes; Morfologi; HSV Classification

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References

S. Rahman, M. Ramli, F. Arnia, R. Muharar, and A. Sembiring, “Performance Analysis of mAlexnet by Training Option and Activation Function Tuning on parking images,” accepted for publication on Journal Of Physics Conference Seies. IOP Publishing, 2020.

S. Rahman, M. Ramli, F. Arnia, A. Sembiring, and R. Muharar, “Convolutional Neural Network Customization for Parking Occupancy Detection,” in 2020 International Conference on Electrical Engineering and Informatics (ICELTICs), Oct. 2020, pp. 1–6, doi: 10.1109/ICELTICs50595.2020.9315509.

S. Rahman and H. Dafitri, “Aplikasi Simulasi Deteksi Lokasi Parkir Kosong Menggunakan Ektraksi Ciri Objek,” InfoTekJar: Jurnal Nasional Informatika dan Teknologi Jaringan, vol. 4, no. 1, pp. 99–104, 2019.

V. Syrris, S. Ferri, D. Ehrlich, and M. Pesaresi, “Image enhancement and feature extraction based on low-resolution satellite data,” Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, vol. 8, no. 5, pp. 1986–1995, 2015.

I. Lubis, H. A. Simamora, S. Rahman, R. Siregar, and H. Lubis, “Aplikasi Edit Foto Background Dengan Menggunakan Metode K-Means Clustering,” Query: Journal of Information Systems, vol. 3, no. 1, 2019.

S. H. W. Tantari, “Pakaian sebagai Pelindung Surya,” Jurnal Kedokteran Brawijaya, vol. 19, no. 2, 2013.

E. Junianto and M. Z. Zuhdi, “Penerapan Metode Palette untuk Menentukan Warna Dominan dari Sebuah Gambar Berbasis Android,” Jurnal Informatika, vol. 5, no. 1, pp. 61–72, 2018, doi: 10.31311/ji.v5i1.2740.

R. Liza, S. Rahman, A. Sembiring, T. M. Diansyah, and H. Dafitri, “Model Efektif Pembelajaran Daring di Masa Pandemi,” Prioritas: Jurnal Pengabdian Kepada Masyarakat, vol. 3, no. 01, pp. 1–6, 2021.

D. Reven and A. T. Ferdinand, “Analisis Pengaruh Desain Produk, Kualitas Produk, Harga Kompetitif, Dan Citra Merek Terhadap Keputusan Pembelian (Studi Pada Pelanggan Nesty Collection Jakarta),” Diponegoro Journal of Management, vol. 6, no. 3, pp. 152–164, 2017.

S. Sengupta, V. Jayaram, B. Curless, S. M. Seitz, and I. Kemelmacher-Shlizerman, “Background matting: The world is your green screen,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 2291–2300.

S. Sundari, E. P. Mardiana, and E. Prabowo, “Implementasi Metode Chroma Key Pada Animasi 3D Prosedur Penyelamatan Diri Dari Kapal Tenggelam,” Query: Journal of Information Systems, vol. 3, no. 1, 2019.

J. B. Xiahou, X. N. Deng, Q. Q. Wei, and X. W. Liu, “Real-Time Video Matting Algorithm Based on Chroma Key,” in Advanced Materials Research, 2014, vol. 926, pp. 3161–3164.

W. Wang and J. Zhao, “Robust image chroma-keying: a quadmap approach based on global sampling and local affinity,” IEEE Transactions on Broadcasting, vol. 61, no. 3, pp. 356–366, 2015.

M. R. Hassan, R. R. Ema, and T. Islam, “Color image segmentation using automated K-means clustering with RGB and HSV color spaces,” Global Journal of Computer Science and Technology, 2017.

G. Saravanan, G. Yamuna, and S. Nandhini, “Real time implementation of RGB to HSV/HSI/HSL and its reverse color space models,” in 2016 International Conference on Communication and Signal Processing (ICCSP), 2016, pp. 462–466.

E. Dougherty, Mathematical morphology in image processing, vol. 1. CRC press, 2018.

S. Rahman, Belajar Teknik Pengolahan Citra dengan Mudah. Yogyakarta: Deepublish, 2018.

J. Serra, “Mathematical morphology,” in Encyclopedia of Mathematical Geosciences, Springer, 2022, pp. 1–16.

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Copyright (c) 2022 Sayuti Rahman, M.F Verri Anggriawan, Rosyidah Siregar, Siti Sundari, Kharunnisa Kharunnisa, Muhammad Zen

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