English Letters Finger Spelling Sign Language Recognition System
Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2014, Vol 10, Issue 7
Abstract
In this paper “English Letters Finger Spelling Sign Language Recognition System” implemented an image processing technique and Neural Network, designed for recognizing the sign language for deaf-dump person. The main objective of this paper is to convert the Fingerspelling image English [26 letters] into English speech for deaf-dump person. It will recognize and identify the finger spelling images which are presented in the English speech. 20 highest DCT coefficients are extracted from each finger spelling and are given as input to SVM model. Support Vector Machine (SVM) is used to recognize the sign (finger spelling) and play and display corresponding English speech and letters. In SVM have three kernels types Polynomial, Gaussian and Sigmoidal it’s applied for Finger spelling recognition into speech.
Authors and Affiliations
D. Karthikeyan , Mrs. G. Muthulakshmi
Keywords
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