Hybrid Topology for Feature Extraction and Classification of Vision Based Hand Gesture Recognition
Muthukumar.K1, Amudha.A2, Gomathy.V3

1Muthukumar. K, Research Scholar, Department of EEE, Karpagam Academy of Higher Education, Coimbatore. (Tamilnadu), India.
2Dr. Amudha. A, Professor & Head, Department of EEE, Karpagam Academy of Higher Education, Coimbatore. (Tamilnadu), India.
3Dr. Gomathy, Associate Professor, Department of EEE, Sri Krishna College of Engineering and Technology, Coimbatore. (Tamilnadu), India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 3360-3365 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7241068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Examining widespread ISL interpretation systems, to formulate a novel vision based HGR algorithm for ISL, to accomplish the proposed algorithm in real time application. Thus, this work is aimed to develop an automatic ISLR for hearing impaired people in India. To attain this, this work formulated the following methodology. An improvised preprocessing topology is designed for the introductory stage. For the segmentation process, skin colour segmentation is carried out. Hybrid topology of feature extraction technique is implemented to identify the vision-based hand gesture recognition. Finally, an efficient ISLR framework was created. Hand gestures (HG) are way of expressions mainly developed for a deaf / speech-impaired person to share their thoughts with others. It is also denoted as a way of exchanging people’s expressions/feeling. Sign Language (SL) is a well-regulated form of HG which comprises signs and visual motions. Hence it is used for communication purpose. These SL are mainly used for a deaf / speech impaired people. Thus, it serves as a tool for their interaction with society. SL delivers its information through various of parts of body viz. hand/fingers/ head and also though body movements/ facial expression. However, SL is not implemented amongst the hearing people and hence only few people can understand it. This results in communication barricade between the deaf/speech-impaired community and the remaining part of the human society. Hence, this problem has yet to be solved. So, the HGR using computer technology has been developed. Thus, this chapter describes about process involved in HGR.
Keyword: Sign Language, Hand Gesture, Local Binary Pattern, Feature Extraction.
Scope of the Article: Classification.