International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

Frequency: 12
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 Volume 5, Issue 6 (June 2018), Pages: 11-18

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 Original Research Paper

 Title: Recognition of static gestures using correlation and cross-correlation

 Author(s): Shazia Saqib *, Syed Asad Raza Kazmi

 Affiliation(s):

 Department of Computer Science, GC University, Lahore, Pakistan

 https://doi.org/10.21833/ijaas.2018.06.002

 Full Text - PDF          XML

 Abstract:

Sign language recognition has been an active area of research for around two decades and numerous sign languages have been extensively studied in order to design reliable sign language recognition systems. Pakistan sign language (PSL) has been used as a case study here. A comprehensive database of static images depicting the signs for different Urdu alphabets is being used as a reference and input images are being compared to perform PSL alphabet recognition. The normalized Correlation technique is being used for image registration between input image and images from the database to find the closest match. The purpose of research is to identify static gestures of any Sign Language which can ultimately lead to an identification of words and sentences. The research starts with image acquisition, image preprocessing, and use of correlation and labeling of an identified symbol. Normalized correlation is used to find the nearest match. This paper includes experiments for 37 static hand gestures related to PSL alphabets. Training dataset consists of 10 samples of each PSL symbol in different lighting conditions, different sizes and shapes of hand by 5 different signers. This gesture recognition system can identify one hand static gestures in any complex background with a “minimum-possible constraints” approach. A comparison is also drawn between normalized correlations and normalized cross-correlation. As compared to other technique, this technique can work with a small dataset size.  The technique is based on unsupervised learning. 

 © 2018 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Sign language, Correlation, Cross correlation, Invariance, Norm correlation, Normalized cross correlation, RGB

 Article History: Received 22 December 2017, Received in revised form 16 March 2018, Accepted 24 March 2018

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2018.06.002

 Citation:

 Saqib S and  Kazmi SAR (2018). Recognition of static gestures using correlation and cross-correlation. International Journal of Advanced and Applied Sciences, 5(6): 11-18

 Permanent Link:

 http://www.science-gate.com/IJAAS/2018/V5I6/Saqib.html

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