Hand-Gesture Recognition-Algorithm based on Finger Counting

The concept of hand gesture recognition has been widely used in communication, artificial intelligence, and robotics. The most contributing reason for the emerging gesture recognition is that they can create a simple communication path between human and computer called HCI (Human-Computer Interaction). Therefore, a hand gesture recognition algorithm was developed for fourteen hand gestures based on finger counting. The algorithm counts fingers and recognizes gesture based on the maximum distance between the fingers detected. The algorithm divided into four main parts: image acquisition, pre-processing, finger detection, and gesture recognition. The experimental results show that the algorithm can count fingers accurately and recognize 10 gestures (associated with 1, 2, 3 and 5 fingers) with good performance (70 to 100 percent of successful detection) and 4 gestures (associated with 4 fingers) with average performance (50 to 70 percent of successful detection). Additionally, the algorithm was tested under variation of the scene and dynamic parameters, to understand its performance further.

[1]  Lizhen Liu,et al.  Image classification via support vector machine , 2015, 2015 4th International Conference on Computer Science and Network Technology (ICCSNT).

[2]  Jr. Joseph J. LaViola,et al.  A Survey of Hand Posture and Gesture Recognition Techniques and Technology , 1999 .

[3]  Nazrul H. Adnan,et al.  Measurement of the flexible bending force of the index and middle fingers for virtual interaction , 2012 .

[4]  H. Seyedarabi,et al.  Real-time dynamic hand gesture recognition using hidden Markov models , 2013, 2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP).

[5]  H. Yabe,et al.  Recognition of gestures using morphological features of networks made of gesture motion images and word sequences , 1999, Proceedings International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems. In Conjunction with ICCV'99 (Cat. No.PR00378).

[6]  Shafriza Nisha Basah,et al.  Gesture-Based Remote-Control System using Coordinate Features , 2015 .

[7]  Jeng-Shyang Pan,et al.  Dominant Points Based Hand Finger Counting for Recognition under Skin Color Extraction in Hand Gesture Control System , 2012, 2012 Sixth International Conference on Genetic and Evolutionary Computing.

[8]  Thomas S. Huang,et al.  Static Hand Gesture Recognition based on Local Orientation Histogram Feature Distribution Model , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[9]  Xiao Han,et al.  Gesture control of ZigBee connected smart home Internet of Things , 2016, 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV).

[10]  Nikos Papamarkos,et al.  Hand gesture recognition using a neural network shape fitting technique , 2009, Eng. Appl. Artif. Intell..

[11]  S. Veluchamy,et al.  Hand gesture recognition system for real-time application , 2014, 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies.

[12]  Dipak Kumar Ghosh,et al.  Static Hand Gesture Recognition Using Mixture of Features and SVM Classifier , 2015, 2015 Fifth International Conference on Communication Systems and Network Technologies.

[13]  Mokhtar M. Hasan,et al.  Robust Gesture Recognition Using Gaussian Distribution for Features Fitting , 2012 .