Vol 8, No 3 (2017) > Electrical, Electronics and Computer Engineering >

Hand Gesture Recognition using Adaptive Network Based Fuzzy Inference System and K-Nearest Neighbor

Fifin Ayu Mufarroha, Fitri Utaminingrum

 

Abstract: The
purpose of the study was to investigate hand gesture recognition. The hand
gestures of American Sign Language are
divided into three categories—namely, fingers gripped, fingers facing upward,
and fingers facing sideways—using the adaptive network-based fuzzy inference
system. The goal of the classification was to speed up the recognition process,
since the process of recognizing
the hand gesture takes a longer time. All pictures in all of the
categories were recognized using K-nearest neighbor. The procedure involved
taking real-time pictures without any gloves or censors. The findings of the
study show that the best accuracy was obtained when the epochs score was 10.
The proposed approach will result in more effective recognition in a short
amount of time.
Keywords: Adaptive Network Based Fuzzy Inference System (ANFIS); American Sign Language (ASL); Hand gesture; K-nearest Neighbor (K-NN)

Full PDF Download

References


Ahmed, A.A.M., Shah, S.M.A., 2015. Application of Adaptive Neuro Fuzzy Inference System (ANFIS) to Estimate the Biochemical Oxygen Demand (BOD) of Surma River. Journal of King Saud University – Engineering Sciences, In Press, Corrected Proof, pp. 1–7

Al-Jarrah, O., Halawani, A., 2001. Recognition of Gesture in Arabic Sign Language using Neuro–Fuzzy System. Artificial Intelligence, Volume 133, pp. 117–138

Bishop, C.M., 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer New York Inc. Secaucus

Deshmukh, R.J., Khule, R.S., 2014. Brain Tumor Detection using Artificial Neural Network Fuzzy Inference System (ANFIS). International Journal of Computer Applications Technology and Research, Volume 3(3), pp. 150–154

Fitri, U., Keiichi, U., Gou, K., 2015. Speedy Filters for Removing Impulse Noise Based on an Adaptive Window Observation. AEU-International Journal of Electronics and Communications, Volume 69(1), pp. 95–100

Ibraheem, N.A., Khan, R.Z., 2012. Vision Based Gesture Recognition using Neural Networks Approaches: A Review. International Journal of Human Computer Interaction (IJHCI), Volume 3(1), pp. 1–14

Jalal, A., Uddin, M.Z., Kim, T.S., 2012. Depth Video-based Human Activity Recognition System using Translation and Scaling Invariant Features for Life Logging at Smart Home. IEEE Transactions on Consumer Electronics, Volume 58(3), pp. 863–871

Jang, J.S.R., 1993. ANFIS: Adaptive Network-based Fuzzy Inference System. IEEE Transactions on Systems, Man, and Cybernetics, Volume 23(3), pp. 665–685

Kotha, S.K., Pinjala, J., Kasoju, K., Pothineni, M., 2015. Gesture Recognition System. IJRET: Internaional Journal of Research in Engineering and Technology, Volume 4(5), pp. 99–104

Naik, S., Metkewar, P., 2015. Recognizing Offline Handwritten Mathematical Expression (ME) based on a Predictive Approach of Segmentation using K-NN Classifier. International Journal of Technology, Volume 3, pp. 345–354

Panwar, M., 2012. Hand Gesture Recognition Based on Shape Parameters. In: 2012 International Conference on Computing, Communication and Applications (ICCCA), Volume 1(6), pp. 22–24

Rekha, J., Bhattacharya, J., Majumder, S., 2011. Hand Gesture Recognition for Sign Language: A New Hybrid Approach. In: The 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV), pp. 80–86

Silarbi, S., Abderrahmane, B., Benyettou, A., 2014. Adaptive Network Based Fuzzy Inference System for Speech Recognition through Subtractive Clustering. International Journal of Artificial Intelligence & Application (IJAIA), Volume 5(6), pp. 43–52

Singh, K., Gupta, I., Gupta, S., 2010. SVM-BDT PNN and Fourier Moment Technique for Classification of Leaf Shape. International Journal of Signal Processing, Image Processing and Pattern Recognition. Volume 3(4). pp. 67–78

Wu, Q., Changle, Z., Chaonan, W., 2006. Feature Extraction and Automatic Recognition of Plant Leaf using Artificial Neural Network. Advances in Artificial Intelligence, Volume 3, pp. 5–12

Zadeh, L.A., 2006. Soft Computing. Available online at www.cs.berkeley.edu/~zadeh