References
Rahaman M A, Jasim M, Zhang T, Ali M H, Hasanuzzaman M. Realtime bengali and chinese numeral signs recognition using contour matching. In: Proceedings of the IEEE International Conference on Robotics and Biomimetics. 2015, 1215–1220
Lü W, Huang J. Skin detection method based on cascaded adaboost classifier. Journal of Shanghai Jiaotong University (Science), 2012, 17(2): 197–202
Xu J, Zhang X. A real-time hand detection system during hand over face occlusion. International Journal of Multimedia and Ubiquitous Engineering, 2015, 10(8): 287–302
Qiu-yu Z, Jun-chi L, Mo-yi Z, Hong-xiang D, Lu L. Hand gesture segmentation method based on YCBCR color space and K-means clustering. International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8(5): 105–116
Iraji M S, Tosinia A. Skin color segmentation in YCBCR color space with adaptive fuzzy neural network (anfis). International Journal of Image, Graphics and Signal Processing, 2012, 4(4): 35–41
Rahaman M A, Jasim M, Ali M H, Hasanuzzaman M. Real-time computer vision based bengali sign language recognition. In: Proceedings of the 17th International Conference on Computer and Information Technology. 2014, 192–197
Yasir F, Prasad P WC, Alsadoon A, Elchouemi A. Sift based approach on bangla sign language recognition. In: Proceedings of the 8th IEEE International Workshop on Computational Intelligence and Applications. 2015, 35–39
Yasir R, Khan R A. Two-handed hand gesture recognition for bangla sign language using LDA and ANN. In: Proceedings of the 8th International Conference on Software, Knowledge, Information Management and Applications. 2014, 1–5
Jasim M, Zhang T, Hasanuzzaman M. A real-time computer vision-based static and dynamic hand gesture recognition system. International Journal on Image and Graphics, 2014, 14(01n02): 1–19
Ayshee T F, Raka S A, Hasib Q R, Hossain M, Rahman R M. Fuzzy rule-based hand gesture recognition for bengali characters. In: Proceedings of the IEEE International Advance Computing Conference. 2014, 484–489
Acknowledgement
This research is partially supported and funded by the Information and Communication Technology (ICT) Division, Ministry of Posts, Telecommunications and IT, Government of the People’s Republic of Bangladesh.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
11704_2018_7082_MOESM2_ESM.pdf
A Real-Time Hand-Signs Segmentation And Classification System Using Fuzzy Rule Based RGB Model And Grid-Pattern Analysis
Rights and permissions
About this article
Cite this article
Rahaman, M.A., Jasim, M., Ali, M.H. et al. A real-time hand-signs segmentation and classification system using fuzzy rule based RGB model and grid-pattern analysis. Front. Comput. Sci. 12, 1258–1260 (2018). https://doi.org/10.1007/s11704-018-7082-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11704-018-7082-4