Published in: International Journal of Computer Applications (IJCA), 2025
HTML: https://www.ijcaonline.org/archives/volume187/number2/hand-gesture-recognition-systems-a-review-of-methods-datasets-and-emerging-trends/
DOI: 10.5120/ijca2025924776
📄 Download Full Paper (PDF)

This peer-reviewed article presents a comprehensive review of Hand Gesture Recognition (HGR) systems — a growing field in human-computer interaction (HCI), with applications in sign language translation, AR/VR, robotics, and assistive technologies.

🔍 Key Contributions:

• Summarizes classical computer vision methods and state-of-the-art deep learning architectures like CNNs, RNNs, and hybrid models.
• Reviews well-known publicly available HGR datasets used in academic and industrial research.
• Discusses critical challenges such as lighting variations, background noise, occlusion, and hand shape diversity.
• Highlights future research directions, including:
  • Multi-modal fusion systems
  • Real-time, low-power implementations
  • Cross-domain generalization techniques

📚 Recommended Citation:

Md Selim Sarowar, Nur E Jannatul Farjana, Md. Asraful Islam Khan, Md Abdul Mutalib, Syful Islam, Mohaiminul Islam.
“Hand Gesture Recognition Systems: A Review of Methods, Datasets, and Emerging Trends.”
International Journal of Computer Applications (IJCA), vol. 187, no. 2, 2025.
DOI: 10.5120/ijca2025924776

📌 IEEE Citation:

Md. S. Sarowar, N. E. J. Farjana, M. A. I. Khan, M. A. Mutalib, S. Islam, and M. Islam,
“Hand Gesture Recognition Systems: A Review of Methods, Datasets, and Emerging Trends,” International Journal of Computer Applications, vol. 187, no. 2, 2025, doi: 10.5120/ijca2025924776.

📄 BibTeX Citation:

@article{ 10.5120/ijca2025924776,
author = { Md Selim Sarowar, Nur E Jannatul Farjana, Md. Asraful Islam Khan, Md Abdul Mutalib, Syful Islam, Mohaiminul Islam },
title = { Hand Gesture Recognition Systems: A Review of Methods, Datasets, and Emerging Trends },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 2 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 1-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number2/hand-gesture-recognition-systems-a-review-of-methods-datasets-and-emerging-trends/ },
doi = { 10.5120/ijca2025924776 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}