SIGN LANGUAGE RECOGNITION USING DEEP LEARNING

SIGN LANGUAGE RECOGNITION USING DEEP LEARNING

Mrs.R.Nivetha, Mrs.P.Vasuki

Department of computer science and engineering, K S R College of Engineering, Tiruchengode, Tamilnadu, India.

Department of computer science and engineering, K S R College of Engineering, Tiruchengode, Tamilnadu, India.

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Abstract - In our society, communication with deaf people is lacking. The introduction of Sign Language (SL) was made in order to get around this obstacle. Sign language uses patterns that are visually transmitted to convey meaning to everyday people. People with autism spectrum disorder (ASD) can also benefit from learning sign language. Because they are unfamiliar with the meaning of each sign, normal people are unable to comprehend the deaf use of language. This issue is intended to be resolved by the proposed system. The camera in this system records a variety of hand gestures. The image is then processed using a variety of algorithms. The image's pre-processing begins first. An edge detection algorithm is then used to determine the edges. Finally, the sign is identified and the text is displayed by a template-matching algorithm. A sign's meaning can be easily deduced because the output is text. Additionally, this makes it easier to communicate with the deaf. Python is used to put the system into action. Various libraries are used by the system.

Key Words:optics, photonics, light, lasers, templates, journals