Hand Gesture Communication for Blind Communication using Raspberry Pi
Punit Dobriyal1, Diparna Adhikary2, Abhimanyu Jain3, G. Rajkumar4
1Punit Dobriyal*, Department of Computer Science & Engineering from SRM Institute of Science & Technology, Chennai, India.
2Diparna Adhikary, Department of Computer Science & Engineering from SRM Institute of Science & Technology, Chennai, India.
3Abhimanyu Jain, Department of Computer Science & Engineering from SRM Institute of Science & Technology, Chennai, India.
4Mr. G Rajkumar, Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 435-438 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5160059720/2020©BEIESP | DOI: 10.35940/ijitee.G5160.059720
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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: HRI represents an obstacle to represent how humans and robots interact. The intricacy is that a robot doesn’t comprehend the human language straightforwardly and HRI requires media for correspondence which can be comprehended by the robot and effortlessly done by human, especially to help old and deaf people, recovering patients, in this manner signal acknowledgment as correspondence media is expected to provide a request to the robot. Machine learning is a fragment of Artificial Intelligence (AI) which discusses the development of a system that depends on information or data. This paper enunciates about the hand signals as input for Bioloid Premium Robot utilizing two strategies, Fuzzy C Means clustering and Support Vector Machine (SVM) with directed acyclic graph (DAG). Here, decision K-Means clustering or Lloyd’s algorithm suggested the way to clustering some data by using the Euclidean idea of distance between all the present data elements.
Keywords: Clustering, Image recognition, Processing, Digital Processing, Robotics, AI
Scope of the Article: Clustering