Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/13306
Title: View-based signer independent approach for indian sign language recognition using extreme learning machine
Researcher: Krishnaveni M
Guide(s): Radha V
Keywords: Computer Science
View-based signer
Indian sign language recognition
Extreme Learning Machine
Upload Date: 27-Nov-2013
University: Avinashilingam Deemed University For Women
Completed Date: March, 2012
Abstract: Sign language is a collection of different kinds of sign pattern to communicate the thoughts of a signer. It is commonly used by the hearing impaired people who neither speak nor hear. As Indian nation has the historical newlinebackground of language movement, it reminds that everyone has the right to communicate using their own language. Similarly, sign language has also been promoted with oral language as an intermediate of interaction and exchanging of ideas. Two approaches are commonly used to recognize gestures in human newlinecomputer interface. One is glove-based and the other is vision-based. The glove-based approach uses gloves and sensors as its measuring device for analyzing the hand movements. This system suffers from the limitation of using a device which is intrusive both for signer and the audience. Vision-based gesture recognition is based on the appearance of the user hand and uses newlinetemplate images or features for its recognition purpose. This approach is newlinetherefore best suited as it is user-friendly and always been a recommended model for gesture analysis. The objective of the proposed research work is to formulate a new viewbased technology for recognition and translation of Indian Sign Language in newlineorder to facilitate the deaf community towards new e-Services. The Indian Sign newlineLanguage has two-hand dominant signs and one-hand dominant signs for letters and numbers. The main focus of the work is on one-hand dominant and to device a recognition approach that can recognize the numeric, vowel, consonant signs using image processing and computational intelligence.
Pagination: 198p.
URI: http://hdl.handle.net/10603/13306
Appears in Departments:Department of Computer Science

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File6.03 kBAdobe PDFView/Open
02_certificate & acknowlegdemnets.pdf233.44 kBAdobe PDFView/Open
03_contents.pdf18.67 kBAdobe PDFView/Open
04_list of figures & tables.pdf293.71 kBAdobe PDFView/Open
05_abstract.pdf630.54 kBAdobe PDFView/Open
06_chapter 1.pdf417.37 kBAdobe PDFView/Open
07_chapter 2.pdf363.97 kBAdobe PDFView/Open
08_chapter 3.pdf384.8 kBAdobe PDFView/Open
09_chapter 4.pdf559.35 kBAdobe PDFView/Open
10_chapter 5.pdf1.59 MBAdobe PDFView/Open
11_chapter 6.pdf650.26 kBAdobe PDFView/Open
12_chapter 7.pdf747.07 kBAdobe PDFView/Open
13_chapter 8.pdf633.84 kBAdobe PDFView/Open
14_chapter 9.pdf1.23 MBAdobe PDFView/Open
15_chapter 10.pdf102 kBAdobe PDFView/Open


Items in Shodhganga are protected by copyright, with all rights reserved, unless otherwise indicated.