Design of Prototypic Army BOT for Landmine Detection and Control using Hand Gestures
Ch. Katyayini1, Shaik Meeravali2
1Ch. Katyayini, Department of Electronics and Communication Engineering, RRS College of Engineering and Technology, JNTU. Hyderabad (Telangana), India.
2Dr. Shaik Meeravali, Department of Electronics and Communication Engineering, RRS College of Engineering and Technology, JNTU. Hyderabad (Telangana), India.
Manuscript received on 21 September 2013 | Revised Manuscript received on 28 September 2013 | Manuscript published on 30 September 2013 | PP: 23-26 | Volume-2 Issue-4, September 2013 | Retrieval Number: D0759092413/2013©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: This paper presents three different gesture recognition models which are capable of recognizing seven hand gestures, i.e., up, down, left, right, tick, circle and cross, based on the input signals from MEMS 3-axes accelerometers. The accelerations of a hand in motion in three perpendicular directions are detected by three accelerometers respectively and transmitted to a PC via Bluetooth wireless protocol. An automatic gesture segmentation algorithm is developed to identify individual gestures in a sequence. To compress data and to minimize the influence of variations resulted from gestures made by different users, a basic feature based on sign sequence of gesture acceleration is extracted. This method reduces hundreds of data values of a single gesture to a gesture code of 8 numbers. Finally the gesture is recognized by comparing the gesture code with the stored templates. Results based on 72 experiments, each containing a sequence of hand gestures (totaling 628 gestures), show that the best of the three models discussed in this paper achieves an overall recognition accuracy of 95.6%, with the correct recognition accuracy of each gesture ranging from 91% to 100%. We conclude that a recognition algorithm based on sign sequence and template matching as presented in this paper can be used for non-specific-users hand-gesture recognition without the time consuming user-training process prior to gesture recognition.
Keywords: Gesture Recognition, Interactive Controller, MEMS Accelerometer, Humidity Sensor.
Scope of the Article: Pattern Recognition