Sign language recognition using image based hand gesture recognition techniques

Nikam, Ashish S.; Ambekar, Aarti G.

doi:10.1109/get.2016.7916786

Cited by 79 publications

(28 citation statements)

References 17 publications

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“…Having observed the number of deaf and dumb people [1] who have difficulty in communicating and the existing systems that don't provide a complete end to end system to eliminate the issue, we decided to develop this solution.…”

Section: Methodsmentioning

confidence: 99%

Sign Language Recognition

Goh¹

2019

IJRTE

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There are nearly 15 million people around the world who have difficulty in speaking or communicating. Their only way of communication is through sign language. Hand gesture is one of the methods used in sign language for non-verbal communication. It is most commonly used by deaf & dumb people who have hearing or speech problems to communicate among themselves or with normal people. There are many recognized sign language standards that have been defined such as ASL(American Sign Language), IPSL(Indo Pakistan Sign Language), etc., which define what sign means what. ASL is the most widely used sign language by the deaf and dumb community. The deaf and dumb use sign language to communicate among themselves with the knowledge of the standard sign language. But they can’t communicate with the rest of the world as most of the people are unaware of the existence and the usage of the sign language. This method aims to remove this communication barrier between the disabled and the rest of the world by recognizing and translating the hand gestures and convert it into speech

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Section: Methodsmentioning

confidence: 99%

Sign Language Recognition

Goh¹

2019

IJRTE

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“…A partir des algorithmes de suivi de mains, des algorithmes de reconnaissance gestuelle peuvent être utilisé pour la reconnaissance de la langue de signes. Nikam et al [25] ont proposé un système en temps réel pour la reconnaissance des gestes de la main sur la base de la détection (par traitement d'image) de certaines caractéristiques et propriété géométriques (l'orientation, le centre de la masse, la position des doigts et le pouce). Shahriar et al [30] ont développé un système de traduction dactylologique ASL (la langue des Signes Américaine) à partir d'un algorithme de segmentation de la peau avec un apprentissage profond (deep learning).…”

Section: Reconnaissance Des Gestes Des Mainsunclassified

A study on the simultaneous consideration of two modalities for the recognition of SoundPainting gestures

Dongo

Jáuregui

Couture

2019

Proceedings of the 31st Conference on l'Interaction Homme-Machine

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“…Sign languages are different from each other and they are not reciprocally comprehensive [29]. Sign languages have distinct rules and elements including both manual and non-manual [35,43].…”

Section: Introductionmentioning

confidence: 99%

Two Dimensional Convolutional Neural Network Approach for Real-Time Bangla Sign Language Characters Recognition and Translation

et al. 2021

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This paper presents a convolutional neural network (CNN) architecture to recognize Bangla Sign Language (BdSL) characters. The proposed CNN architecture also translates the recognized signs into respective textual Bangla characters and provides real-time prediction. The automatic recognition and translation of sign language make communication between dumb and deaf and normal people natural. The recognition structure is validated with a dataset of a total of 4600 selected hand sign images collected from volunteers using an HD Webcam. The proposed structure guarantees the functionality of enhancing the directed dataset by capturing new images of variant persons in real-time. The proposed model recognizes all the 36 letters and 10 digits of the BdSL with significant accuracy. A state-of-the-art result with a validation accuracy of 99.57% and a validation loss of 0.56% has been achieved in the recognition and translation of the BdSL characters.

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Sign language recognition using image based hand gesture recognition techniques

Cited by 79 publications

References 17 publications

Sign Language Recognition

Sign Language Recognition

A study on the simultaneous consideration of two modalities for the recognition of SoundPainting gestures

Two Dimensional Convolutional Neural Network Approach for Real-Time Bangla Sign Language Characters Recognition and Translation

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