Abstract
In this work, we propose two novel approaches to classify sign images based on their skeletons. In the first approach, the distance features are extracted from the endpoints and junction points remarked on the skeleton. The extracted features are aggregated by the use of interval-valued type data and are saved in the knowledge base. A symbolic classifier has been used for the purpose of classification. In second approach, the concept of spatial topology is combined with the symbolic approach for classifying the sign gesture skeletons. From the end points and junction points of skeletons, triangles are generated using Delaunay Triangulation; and for each triangle, features like lengths of each side and angles are extracted. These extracted features of each skeleton of signs are clumped and represented in the form of interval-value type data. A suitable symbolic classifier is designed for the purpose of classification. Experiments are conducted on our own real dataset to evaluate the performance of two approaches. The experimental results disclose the success of the proposed classification approach.
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References
Sawant, SN.: Sign Language recognition system to aid deaf-dumb people using PCA. Int. J. Comput. Sci. Eng. Technol. (IJCSET) vol. 5, No. 05 (2014)
Sharma, R., Goyal, S., Sharma, I., Sharma, S., Kane, L., Khanna, P.: Recognition of single handed sign language using contour descriptor. In Proceedings of World Congress on Engineering (WCE) vol. 2, (2013)
Goyal, S., Sharma, I., Sharma, S.: Sign language recognition system for deaf and dumb people. In: Proceedings of International Journal of Engineering Research & Technology (IJERT) vol. 2, Issue 4, (2013)
Singha, J., Das, K.: Indian Sign language recognition using eigen value weighted euclidean distance based classification technique. Int. J. Adv. Comput. Sci. Appl. 4(2) (2013)
Singha, J., Das, K.: Recognition of Indian sign language in live video. Int. J. Comput. Appl. 70(19) (2013)
Dixit, K., Jalal, A.S.: Automatic Indian sign language recognition system. In: 3rd IEEE International Advance Computing Conference (IACC), (2013)
Bhuyan, M.K.: FSM-based recognition of dynamic hand gestures via gesture summarization using key video object planes. Int. Sci. Index 6(8) (2012)
Subha Rajam, P., Balakrishnan, G., Dr..: Real time Indian sign language recognition system to aid deaf-dumb people. In: proceedings of IEEE International Conference on Communication Technology (ICCT), (2011)
Shukla, J., Dwivedi, A.: A Method for hand gesture recognition. In: Proceedings of IEEE International Conference on Computer system and Network Technologies (CSNT), (2014)
Billard, L., Diday, E.: Symbolic data analysis—conceptual statistics and data mining. Wiley Series In Computational Statistics (Wiley, Chichester 2006)
Gonzalez, R.C., Woods, R.E. Eddins, S.L.: Digital image processing using MATLAB. (Prentice-Hall, Inc., Upper Saddle River 2003)
Bai, L., Latecki, J., Liu, W.Y.: Skeleton pruning by contour partitioning with discrete curve evolution, IEEE Trans. Patt. Anal. Mach. Intell. 29(3) 449–462 (2007)
Guru, D.S., Prakash, H.N.: Online signature verification and recognition an approach based on symbolic representation. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1059–1073 (2009)
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Sharath Kumar, Y.H., Vinutha, V. (2016). Hand Gesture Recognition for Sign Language: A Skeleton Approach. In: Das, S., Pal, T., Kar, S., Satapathy, S., Mandal, J. (eds) Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015. Advances in Intelligent Systems and Computing, vol 404. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2695-6_52
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DOI: https://doi.org/10.1007/978-81-322-2695-6_52
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