Development of Virtual Painting Method using OpenCV Library with Finger Gesture on Online Learning Platform

Glenn Ramadhan, Jansen Wiratama, Angga Aditya Permana


With the pandemic situation that has occurred for the last two years to date, educators and students carry out many learning activities online. Learning activities are carried out using virtual meeting media, the concept of meetings and discussion processes that are carried out virtually with existing digital communication devices. From the problems, it was found that students were likelier to be less active when learning theory than practice, which made it difficult for educators to find various media that would be given to students to support online learning activities to be more interactive. This study discusses the creation of a system that can be a medium for delivering helpful material to improve the quality of interaction between educators and students. A virtual painter is one of the media to support the online interactive learning process, where educators can complete the material presented with a clearer picture that educators provide to students. Virtual painters are used to tracking finger pattern movements where the user moves his hand as needed, namely drawing and release, which educators can use to deliver more interactive material to students in theoretical and practical learning. The system design method used in building the virtual painting is Rapid Application Development (RAD) which is carried out through 8 stages, starting from Requirements Analysis to Operation and Maintenance. Next, the diagram design uses UML notation and the phyton with OpenCV coding process. After the virtual painter had been made, an evaluation was conducted and resulted in a positive impression of all six scales: attractiveness, efficiency, clarity, precision, stimulation, and novelty.

Full Text:



Budijono, S., & Tanutama, L. (2021). Virtual Face to Face Meeting for Non-Technical Personnel. Social Economics and Ecology International Journal (SEEIJ), 4(1), 1–8.

Dennis, Alan, Barbara Wixom, D. T. (2015). Systems analysis and design: An object-oriented approach with UML (E. K. Beth Lang Golub, Mary O’Sullivan (ed.); 5th Editio). Don Fowley.

Hafeez, A., Ahmed, M., Furqan, M., Rehaman, W.-U.-, & Husain, I. (2019). Importance and Impact of Class Diagram in Software Development. Indian Journal of Science and Technology, 12(25), 1–4.

Hasibuan, S. A., & Damanik, L. A. (2020). Metode Pembelajaran Interaktif yang Diselenggarakan Secara Daring Akibat Mewabahnya Covid-19. 182–188.

Ismail, A. P., Aziz, F. A. A., Kasim, N. M., & Daud, K. (2021). Hand gesture recognition on python and opencv. IOP Conference Series: Materials Science and Engineering, 1045(1), 012043.

Kaesmetan, Y., & Overbeek, M. (2022). Digital Image Processing using Texture Features Extraction of Local Seeds in Nekbaun Village with Color Moment, Gray Level Co Occurance Matrix, and k-Nearest Neighbor. Ultimatics : Jurnal Teknik Informatika, 13(2), 81-88.

Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M. G., Lee, J., Chang, W.-T., Hua, W., Georg, M., & Grundmann, M. (2019). MediaPipe: A Framework for Building Perception Pipelines.

M, S. (2020). The Effectiveness of Using the ZOOM Cloud Meetings Application in the Learning Process. Proceeding of The International Conference on Science and Advanced Technology (ICSAT), 590–602.

Maharani, Y. S., Suryani, N., & Ardianto, D. T. (2018). Pengembangan Multimedia Pembelajaran Interaktif Pada Mata Pelajaran Pengolahan Citra Digital di Sekolah Menengah Kejuruan Negeri 8 Semarang. Teknodika, 16(1), 73.

Mazda, C. N., & Fikria, A. N. (2021). Analisis Efektifitas Google Classroom , Zoom Meeting dan Google Meet sebagai Multimedia Interaktif Pembelajaran Online. 8106, 1–9.

Patil, Y., Paun, M., Paun, D., Singh, K., & Borate, V. K. (2020). Virtual Painting with Opencv Using Python. 5(8), 189–194.

Pricillia, T., & Zulfachmi. (2021). Perbandingan Metode Pengembangan Perangkat Lunak. Survey Paper, X(01), 6–12.

Primož Podržaj, & Boris Kuster. (2018). Possibilities of Python Based Emotion Recognition. 31–40.

Pulungan, A. B., Nafis, Z., Anwar, M., Hastuti, Hamdani, & -, D. E. M. (2021). Object Detection with a Webcam Using the Python Programming Language. Journal of Applied Engineering and Technological Science (JAETS), 2(2), 103–111.

Saurabh et al., (2021). Basic Paint Window Application via Webcam Using OpenCV and Numpy in Python. Journal of Interdisciplinary Cycle Research Volume XIII, Issue VII, July/2021.

Srungavarapu, P., Maganti, E. P., Sakhamuri, S., Veerada, S. P. K., & Chinta, A. (2021). Virtual Sketch using Open CV. International Journal of Innovative Technology and Exploring Engineering, 10(8), 107–108.

Suryadibrata, A., & Young, J. (2020). Visualisasi Algoritma sebagai Sarana Pembelajaran K-Means Clustering. Ultimatics : Jurnal Teknik Informatika, 12(1), 25-29.

Vakunov, F. Z. V. B. A., & Grundmann, A. T. G. S. C.-L. C. M. (2020). MediaPipe Hands: On-device Real-time Hand Tracking.

Wahyudi, I., Bahri, S., & Handayani, P. (2019). Aplikasi Pembelajaran Pengenalan Budaya Indonesia. V(1), 135–138.

Zein, A. (2018). Pendeteksian Kantuk Secara Real Time Menggunakan Pustaka OPENCV dan DLIB PYTHON. Sainstech: Jurnal Penelitian Dan Pengkajian Sains Dan Teknologi, 28(2), 22–26.


Article Metrics

Abstract - 342 PDF - 244


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.