Hand Gesture Object Recognition Based on the combination of Fuzzy Reasoning Method, Back propagation Algorithm and Mamdani Classification Approach
Samta Jain Goyal1, Arvind Kumar Upadhyay2, Rakesh Singh Jadon3
1Samta Jain Goyal, Department of CSE, Amity University, (Madhya Pradesh), India.
2Dr. A.K. Upadhyay, Department of CSE, Amity University, (Madhya Pradesh), India.
3Dr. R.S. Jadon, Department of MCA, MITS, Gwalior, (Madhya Pradesh), India
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 505-509 | Volume-8 Issue-5, March 2019 | Retrieval Number: E2968038519/19©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: In present scenario, the importance of Hand Gesture Object Recognition is widely used in many real time applications. HGOR System is basically a combination of The Fuzzy Reasoning System (FRS), Artificial Neural Network (ANN) with the Fuzzy Measure classifiers. The purpose of this work is to investigate and develop more effective and more accurate system than the earlier developed System. The purpose of this system is to speed up the recognition process because these systems take more training and testing time. This work presents a method for HGOR for the Static hand position to get the meaning for machine interaction. Also, this work is used for facial expression recognition based on hand gesture position surrounding the face to get better position for communication through machine in HCI.
Keyword: Artificial Neural Network (ANN), Fuzzy Reasoning System (FRS), Fuzzy Measure Classifier, Hand Gesture Object Recognition (HGOR), Human-Computer Interaction (HCI), Mamdani Classification.
Scope of the Article: Classification