An Improved Hand Gesture Recognition System Based on Optimized MSVM and SIFT Feature Extraction Algorithm

In today’s robotics and machine translation tasks are performing the main role in hand gestures. Gesture or detection implementation will help humans in several means. Gesture recognition systems are used in various fields such as DNN, ML and NNs etc. The applications of this research are sign language translation, music creation and Robot remote controlling, etc. In this research work proposed HGR methods are using feature extraction and optimized MSVM classification. This process gives the applications of edge detection, interference, filters, SIFT-ALO algorithm and binary during image pre-processing, in which these approaches add to better extraction and selection. In proposed work, implemented an optimized MSVM method are two classes such as training and testing. Optimized M-SVM is performed on the ASL gesture dataset along with existing SURF and SIFT techniques. This research work is used for the simulation tool (MATLAB) and calculated performance metrics like processing time, error rate and accuracy rate with the MSVM value at 99.1 percent as compared to existing feature extraction methods.

[1]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[2]  M. S. Sahane,et al.  Visual Interpretation Of Hand Gestures For Human Computer Interaction , 2014 .

[3]  T. Prem Jacob,et al.  Hand Gesture Recognition and Implementation for Disables using CNN’S , 2019, 2019 International Conference on Communication and Signal Processing (ICCSP).

[4]  Shaoming Pan,et al.  Hand Gesture Recognition with Skin Detection and Deep Learning Method , 2019, Journal of Physics: Conference Series.

[5]  Hong Dai.  Research on SVM improved algorithm for large data classification , 2018, 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA).

[6]  Shigeo Abe.  Support Vector Machines for Pattern Classification , 2010, Advances in Pattern Recognition.

[7]  Mohamed Alsheakhali,et al.  Hand Gesture Recognition System , 2011 .

[8]  Napoleon H. Reyes,et al.  A New 2D Static Hand Gesture Colour Image Dataset for ASL Gestures , 2011 .

[9]  Runqing Zhang,et al.  Hand gesture recognition with SURF-BOF based on Gray threshold segmentation , 2016, 2016 IEEE 13th International Conference on Signal Processing (ICSP).

[10]  Abdelhak Mahmoudi,et al.  Machine learning for hand gesture recognition using bag-of-words , 2018, 2018 International Conference on Intelligent Systems and Computer Vision (ISCV).