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Original Article
Hand Sign Language Recognition using Zernike Moments– Based Feature Extraction and Machine Learning Classification
Yogesh S.Rode1
Siddharth Dabhade2
1 Jijamata Mahavidyalaya, Buldhana, Maharashtra, India. 2 National Forensic Sciences, University, Gandhinagar, Gujarat, India.
Published Online: May-August 2026
Pages: 814-818
Cite this article
No DOIReferences
1. Sumit Kumar, Ruchi Rani, Ulka Chaudhari, Real-time sign language detection: Empowering the disabled community, MethodsX, Volume
13, December 2024, ISSN 2215-0161,
2. T. Starner and A. Pentland, “Real-time American Sign Language recognition from video using hidden Markov models,” Proc. IEEE Int.
Symp. Computer Vision, Coral Gables, FL, USA, pp. 265–270, 1995.
3. Karbhari V Kale, Prapti D Deshmukh, Shriniwas V Chavan, Majharoddin M Kazi, Yogesh S Rode, “Zernike Moment Feature Extraction for
Handwritten Devanagari (Marathi) Compound Character Recognition”. International Journal of Advanced Research in Artificial Intelligence
(IJARAI) 3.1 ,2014.
4. Biswas, Sougatamoy (2024), “ISL Hand Gesture Dataset”, Mendeley Data, V1, doi: 10.17632/n34wm8sb3x.1.
5. Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing etc.,”The State-of-the-Art Review on Applications of Intrusive Sensing, Image
Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis”,Engineering,Volume 7, Issue 6, 2021,Pages
845-856, ISSN 2095-8099,
6. Lei Zou, Baoye Song, Jinghui Suoa, Na Li and Chenxi Wang, “A survey on outlier-resistant state estimation and its applications”, Systems
Science & Control Engineering: An Open Access Journal, 2025, VOL. 13, NO. 1, 2474471,pp 1-17.
7. Bo Yuan, Chew Lim Tan, Convex hull based skew estimation, Elsevier, Pattern Recognition, Volume 40, Issue 2, 2007, Pages 456-475, ISSN
0031-3203.
8. Kaustubh Wani, S. Ramya, “Hand Gesture Recognition Using Convex Hull-Based Approach”, Advances in Communication, Devices and
Networking - Proceedings of ICCDN 2020, pp. 161-170, Lecture Notes in Electrical Engineering; Vol. 776. Springer Science.
9. Whoi-Yul Kim, Yong-Sung Kim,”A region-based shape descriptor using Zernike moments, Signal Processing: Image
Communication”,Volume 16, Issues 1–2, 2000,Pages 95-102, ISSN 0923-5965.
10. Aneta G´orniak, Ewa Skubalska-Rafaj,” Object classification using sequences of Zernike moments”, 16th IFIP International Conference on
Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. pp.99-109, HAL Open Science.
13, December 2024, ISSN 2215-0161,
2. T. Starner and A. Pentland, “Real-time American Sign Language recognition from video using hidden Markov models,” Proc. IEEE Int.
Symp. Computer Vision, Coral Gables, FL, USA, pp. 265–270, 1995.
3. Karbhari V Kale, Prapti D Deshmukh, Shriniwas V Chavan, Majharoddin M Kazi, Yogesh S Rode, “Zernike Moment Feature Extraction for
Handwritten Devanagari (Marathi) Compound Character Recognition”. International Journal of Advanced Research in Artificial Intelligence
(IJARAI) 3.1 ,2014.
4. Biswas, Sougatamoy (2024), “ISL Hand Gesture Dataset”, Mendeley Data, V1, doi: 10.17632/n34wm8sb3x.1.
5. Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing etc.,”The State-of-the-Art Review on Applications of Intrusive Sensing, Image
Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis”,Engineering,Volume 7, Issue 6, 2021,Pages
845-856, ISSN 2095-8099,
6. Lei Zou, Baoye Song, Jinghui Suoa, Na Li and Chenxi Wang, “A survey on outlier-resistant state estimation and its applications”, Systems
Science & Control Engineering: An Open Access Journal, 2025, VOL. 13, NO. 1, 2474471,pp 1-17.
7. Bo Yuan, Chew Lim Tan, Convex hull based skew estimation, Elsevier, Pattern Recognition, Volume 40, Issue 2, 2007, Pages 456-475, ISSN
0031-3203.
8. Kaustubh Wani, S. Ramya, “Hand Gesture Recognition Using Convex Hull-Based Approach”, Advances in Communication, Devices and
Networking - Proceedings of ICCDN 2020, pp. 161-170, Lecture Notes in Electrical Engineering; Vol. 776. Springer Science.
9. Whoi-Yul Kim, Yong-Sung Kim,”A region-based shape descriptor using Zernike moments, Signal Processing: Image
Communication”,Volume 16, Issues 1–2, 2000,Pages 95-102, ISSN 0923-5965.
10. Aneta G´orniak, Ewa Skubalska-Rafaj,” Object classification using sequences of Zernike moments”, 16th IFIP International Conference on
Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. pp.99-109, HAL Open Science.
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