The week's pick
Random Articles
Reseach Article
Hand Gesture Recognition using Machine Learning with Convolutional Neural Network (CNN)
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 16 |
| Year of Publication: 2022 |
| Authors: Shubham A. Sangale, R.M. Samant, Narayan B. Kirtane, Avinash A. Bhatane, Madhuri S. Jagtap |
10.5120/ijca2022922159
|
Shubham A. Sangale, R.M. Samant, Narayan B. Kirtane, Avinash A. Bhatane, Madhuri S. Jagtap . Hand Gesture Recognition using Machine Learning with Convolutional Neural Network (CNN). International Journal of Computer Applications. 184, 16 ( Jun 2022), 29-32. DOI=10.5120/ijca2022922159
Abstract
Many deaf and hard-of-hearing people rely heavily on sign languages as a means of communication. Sign languages are the native languages of the Deaf community and provide full access to communication. Despite the fact that it is an effective mode of communication, communicating with speech impaired people remains a barrier for those who do not understand sign language. The purpose of this paper is to create a Web application that will convert hand gesture to English in the form of text. hence facilitating sign language communication. The web application uses the computer's webcam to collect visual data, which is then pre-processed using a combinational method before being recognized via template matching. This project tried different machine learning algorithms including SVM, RNN and CNN (Convolutional Neural Network). With the accuracy of 91% CNN algorithm has proven to be the most accurate classification tool.
References
- K. Bantupalli and Y. Xie, "American Sign Language Recognition using Deep Learning and Computer Vision," 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 4896-4899, doi: 10.1109/BigData.2018.8622141.
- Jaoa Carriera, A. Z. (2018). Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on (pp. 4724-4733). IEEE. Honolulu.
- Jing-Hao Sun, Ting-Ting Ji, Shu-Bin Zhang, Jia-Kui Yang, Guang-Rong Ji "Research on the Hand Gesture Recognition Based on Deep Learning",07 February 2019.
- Chaudhuri, Arindam and Mandaviya, Krupa and Badelia, Pratixa and Ghosh, Soumya K and others. (2017) “Optical Character Recognition System. In Optical Character Recognition Systems for Different Languages with Soft ComputingSpringer: 941.
- Li, Haixiang and Yang, Ran and Chen, Xiaohui. (2017) “License plate detection using convolutional neural network. 3rd IEEE International Conference on Computer and Communications (ICCC),IEEE:17361740.
- Geethu G Nath and Arun C S, "Real Time Sign Language Interpreter," 2017 International Conference on Electrical, Instrumentation, and Communication Engineering (ICEICE2017).
- Sanmukh Kaur, Anuranjana (2018), “Electronic Device Control Using Hand Gesture Recognition System for Differently Abled”, 8th International Conference on Cloud Computing, Data Science & Engineering.
- Saransh Sharma, Samyak Jain, Khushboo (2019), “A Static Hand Gesture and Face Recognition System for Blind People”, 6th International Conference on Signal Processing and Integrated Networks.
- Anush Ananthakumar (2018), “Efficient Face and Gesture Recognition for Time Sensitive Application”, IEEE Southwest Symposium on Image Analysis and Interpretation.
- Brownlee, J.,2019. Deep Learning for Computer Vision: Image Classification, Object Detection, and Face Recognition in Python. Machine Learning Mastery
Index Terms
Keywords