Research on Chinese sign language recognition based on skeleton features

Abstract

The hearing-impaired people in China account for about 20% of the world ’s hearingimpaired people, and increase year by year. Chinese sign language is an important auxiliary tool for communication between the hearing impaired and the outside world. Finger language is a part of sign language, the number of it is not large and it is easy to learn and remember. Therefore, this thesis takes. Chinese letter sign language as the research object, studies Chinese letter sign language in different backgrounds, and researches the skeleton extraction of gesture images, the presentation and recognition of skeleton descriptors based on computer vision. The main research content of this thesis is Chinese letter sign language recognition based on skeleton features. Firstly, gestures are extracted. Secondly, on the basis of the extracted binary image of gestures, an improved gesture skeleton extraction method based on distance change is proposed to make the extracted skeletons have connectivity.