Hand Calculator System using Convolutional Neural Networks
Y. Jhansi1, U. Harish2

1Dr. Y.Jhansi, Department of Computer Science and Engineering, GITAM Institute of Technology, Visakhapatnam (A.P), India.
2U. Harish, Department of Information Technology, GITAM Institute of Technology, Visakhapatnam (A.P), India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 114-118 | Volume-8 Issue-5, January 2020. | Retrieval Number: D9106118419/2020©BEIESP | DOI: 10.35940/ijrte.D9106.018520

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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: Computer vision has great attention in recent years as it identifies and similarly processes images that human vision does and they provide suitable output. In computer vision, hand gesture recognition is one of the important and fundamental problems. The hand gesture recognition system has gained significant importance in the recent few years because of its manifoldness applications. This paper aims to give a new approach for vision-based, fast and real time hand gesture recognition, a new light that can be used in many HCI applications. The proposed algorithm first detects and segments the hand region and by using our innovative approach, it finds the fingers and classifies the gesture. The proposed algorithm is invariant to orientation, hand position or distance from the webcam. Based on this proposed algorithm we have progressively developed a gesture-based mathematical tool (calculator) as a practical application.
Keywords: Computer Vision, Human-Computer Interaction (HCI), Gesture Recognition, Convolutional Neural Network (CNN).
Scope of the Article: Advanced Computer Networking.