Recognition of Hand Gesture for a Paralytic Person Using Convolutional Neural Network
A.Naga Harshita1, Azhagiri M2, G.Sri Krishna Priya3, Khadijah S Sabu4
1A.Naga Harshita*, Computer Science, SRM Institute of Scince And Technology, Ramapuram Campus, Chennai, India.
2Azhagiri M, Computer Science, SRM Institute of Scince And Technology, Ramapuram Campus, Chennai, India.
3G.Sri Krishna Priya, Computer Science, SRM Institute of Scince And Technology, Ramapuram Campus, Chennai, India.
4Khadijah S Sabu, Computer Science, SRM Institute of Scince And Technology, Ramapuram Campus, Chennai, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 3169-3173 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9866109119/2019©BEIESP | DOI: 10.35940/ijeat.A9866.109119
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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: According to the Indian statistics, the stroke rate is higher compared to other countries. It is approximately 1.8 million Indians out of 1.2 billion Indians suffering from stroke every year. As a result of this brain cells get damaged which leads to paralysis. To help the stroke patients out of its researchers have found a solution by creating hand gestures that will help them perform daily functions easily. The gesture made by hand will be the input instead of a mouse or keyboard. The main aim is to read and detect the hand gestures by using high-resolution cameras and process the images using convolution neural networks by the process of edge detection.
Keywords: Hand gesture, Convolution Neural Network, Edge Detection.