Sign language number recognition

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Conference Proceeding

Source Title

NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC

First Page

1503

Last Page

1508

Publication Date

12-1-2009

Abstract

Sign language number recognition system lays down foundation for handshape recognition which addresses real and current problems in signing in the deaf community and leads to practical applications. The input for the sign language number recognition system is 5000 Filipino Sign Language number video file with 640 x 480 pixels frame size and 15 frame/second. The color-coded gloves uses less color compared with other color-coded gloves in the existing research. The system extracts important features from the video using multi-color tracking algorithm which is faster than existing color tracking algorithm because it did not use recursive technique. Next, the system learns and recognizes the Filipino Sign Language number in training and testing phase using Hidden Markov Model. The system uses Hidden Markov Model (HMM) for training and testing phase. The feature extraction could track 92.3% of all objects. The recognizer also could recognize Filipino sign language number with 85.52% average accuracy. © 2009 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/NCM.2009.357

Disciplines

Computer Sciences

Keywords

Computer vision; Sign language; Pattern recognition systems; Human-computer interaction

Upload File

wf_no

This document is currently not available here.

Share

COinS