Rotation Invariant Technique for Sign Language Recognition
DOI:
https://doi.org/10.51173/ijds.v1i1.6Keywords:
Sign language, Contourlet Transform, Deep Learning, RotationAbstract
Sign language recognition is an assistive technology that has garnered significant attention from researchers, particularly with respect to its potential benefits for individuals with hearing impairments. This paper proposes an effective technique for sign language recognition based on the Contourlet Transform (CT) and deep learning. The CT is employed in the pre-processing stage to reduce complexity and processing time, while deep learning is utilized to extract and classify sign language features. The proposed method was evaluated using two sign language databases: a direct feed database and an American sign language database. The experimental analysis demonstrated that the proposed method gives good results in processing time by more than 70% while maintaining high accuracy
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