Two-handed hand gesture recognition for Bangla sign language using LDA and ANN

Author

Yasir, Rahat ; Khan, Riasat Azim

Author_Institution

Comput. Sci. & Eng., North South Univ., Dhaka, Bangladesh

fYear

2014

Firstpage

1

Lastpage

5

Abstract

Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users by computer vision. In this respect, an efficient method is proposed consists of some significant steps and they are, skin detection, preprocessing, different machine learning techniques like PCA and LDA, neural network for training and testing purpose of the system. Various hand sign images are used to test the proposed method and results are presented to provide its effectiveness.

Keywords

computer vision; learning (artificial intelligence); neural nets; object detection; principal component analysis; sign language recognition; ANN; Bangla sign language; LDA; PCA; SLDR; computer vision; linear discriminant analysis; machine learning techniques; neural network; preprocessing; principal component analysis; sign language detection and recognition; skin detection; two-handed hand gesture recognition; Assistive technology; Feature extraction; Gesture recognition; Principal component analysis; Skin; Testing; Training; Back propagation Neural Network; LDA; PCA; YCbCr; hand gesture; sign language;

fLanguage

English

Publisher

ieee

Conference_Titel

Software, Knowledge, Information Management and Applications (SKIMA), 2014 8th International Conference on

Type

conf

DOI

10.1109/SKIMA.2014.7083527

Filename

7083527