Intelligent Image Processing System Based on Virtual Painting

Samira Abdul-Kader Hussain

doi:10.37899/journallamultiapp.v3i6.754

Samira Abdul-Kader Hussain Computer Science Department, Collage of Science,Mustansiriyah University, Baghdad-Iraq

DOI: https://doi.org/10.37899/journallamultiapp.v3i6.754

Keywords: Image Processing, Artificial Intelligence, Virtual Painting, Opencv, Media Pipe

Abstract

Image processing and artificial intelligence have come so far in the age of technology that they are now used in every field. AI is meant to help people do their jobs better and with less help. Virtual painting is a clever tool that lets us paint by just moving our hands. This app uses hand tracing and finger movement recording to show marks. With this program, we can open the camera on our computer or laptop and draw with our hands, colored pens, or pens we made ourselves. Image processing is used to figure out how the hand is moving. This turns the person in front of the camera into a great illustrator who can pick out colors and draw in similar directions on the screen. OpenCV, which is the brain of the system, and Media Pipe have been added to this application.

References

Baxter, B., Scheib, V., Lin, M. C., & Manocha, D. (2001). DAB: Interactive haptic painting with 3D virtual brushes. Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2001, 461–468. https://doi.org/10.1145/383259.383313

Beyeler, M. (2015). OpenCV with Python blueprints. Packt Publishing Ltd

Gaikwad, G., Sonawane, V., Sonawane, S., & Khadke, P. (2022). Virtual painting. 05, 1198–1201.

Ibrahim, M. K., Hussien, N. M., & Alsaad, S. N. (2021). Smart system for monitoring ammonium nitrate storage warehouse. Indonesian Journal of Electrical Engineering and Computer Science, 23(1), 583–589. https://doi.org/10.11591/ijeecs.v23.i1.pp583-589

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. https://doi.org/10.1088/1757-899x/1045/1/012043

Knispel, J., & Bullock, F. (2017). SIGGRAPH Asia 2017 VR Showcase, SA 2017. SIGGRAPH Asia 2017 VR Showcase, SA 2017, 1–2. https://research-repository.uwa.edu.au/en/publications/collaborative-vr-painting-in-web-browsers

Konieczny, J., Heckman, J., Meyer, G., Manyen, M., Rabens, M., & Shimizu, C. (2008). Automotive spray paint simulation. In Advances in Visual Computing: 4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part I 4 (pp. 998-1007). Springer Berlin Heidelberg.‏

Kumaravel, B. T., Nguyen, C., DiVerdi, S., & Hartmann, B. (2019). TutoriVR: A video-based tutorial system for design applications in virtual reality. Conference on Human Factors in Computing Systems - Proceedings, September. https://doi.org/10.1145/3290605.3300514

Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., ... & Grundmann, M. (2019, June). Mediapipe: A framework for perceiving and processing reality. In Third Workshop on Computer Vision for AR/VR at IEEE Computer Vision and Pattern Recognition (CVPR) (Vol. 2019)

Tian, L. (2022). Analysis of Chinese Painting Color Teaching Based on Intelligent Image Color Processing Technology in the Network as a Green Environment. Journal of Environmental and Public Health, 2022. https://doi.org/10.1155/2022/8303496

Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.-L., & Grundmann, M. (2020). MediaPipe Hands: On-device Real-time Hand Tracking. http://arxiv.org/abs/2006.10214.