Abstract
The sign language that comprises of various sign patterns is an effective communication medium to convey message, disseminate knowledge and transfer ideas among the deaf people. Understanding of such sign signals and positive responses for the benefit deaf people using intelligent machine learning strategy is essential in the technological era. The objective of this chapter to addresses an optimized Automatic Tamil Sign Language Recognition (ATSLR) framework with natural inspired computing paradigm employing image processing technique for recognition of TSL patterns in computer vision application. The algorithm has been validated with local regional signs of Tamil Language. Algorithm aftermaths and comparison analysis in the context of state-of-art methods reveals the effectiveness of the proposed method. The real time Tamil Sign Language (TSL) images have taken for experimentation include 12 vowels, 1 Aayutha Ezhuthu and 18 consonants representation from 110 different signers and the experimental outcomes demonstrated its effectiveness.
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Krishnaveni, M., Subashini, P., Dhivyaprabha, T.T. (2019). An Assertive Framework for Automatic Tamil Sign Language Recognition System Using Computational Intelligence. In: Hemanth, J., Balas, V. (eds) Nature Inspired Optimization Techniques for Image Processing Applications. Intelligent Systems Reference Library, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-96002-9_3
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