Spelled sign word recognition using key frame | Zendy

Rokade Rajeshree S. | Zendy; Doye Dharmpal D. | Zendy

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Spelled sign word recognition using key frame

Author(s) -

Rokade Rajeshree S.,

Doye Dharmpal D.

Publication year - 2015

Publication title -

iet image processing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.401

H-Index - 45

eISSN - 1751-9667

pISSN - 1751-9659

DOI - 10.1049/iet-ipr.2012.0691

Subject(s) - computer science , word (group theory) , sign (mathematics) , frame (networking) , key (lock) , speech recognition , artificial intelligence , key frame , natural language processing , pattern recognition (psychology) , mathematics , telecommunications , computer security , mathematical analysis , geometry

In this study, the authors present a new system for sign language hand gesture recognition. Using video input, the system can recognise any spelled word or alphabetic sequence signed in American Sign Language. The three main steps in the recognition process include detection of the region of interest (the hands), detection of key frames and recognition of gestures from these key frames. The proposed segmentation algorithm distinguishes regions of interest from both uniform and non‐uniform backgrounds with an efficiency of 95%. The proposed key frame detection algorithm achieves an efficiency of 96.50%. A rotation‐invariant algorithm for feature extraction is additionally proposed, which provides an overall gesture recognition efficiency of 84.2%.

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