Many authors have proposed various image processing and Machine Learning (ML) techniques for sign language recognition. Some of the relevant works have been discussed here in the middle of the 1970s, Myron W. Krueger originally suggested gesture recognition as a brand-new method of communication between people and computers. With the rapid advancement of computer hardware and vision systems over the last few years, it has emerged as a very significant study topic.
It discussed how to use grayscale images and edge detection techniques to detect hand gestures. The drawback of this technique is that there are some limitations when it comes to grayscale images as they are only 2D data and it is difficult to extract the key features of the hand by Sammon Babu [1]
He introduced a technique to recognize hand gestures using a leap motion controller which is quite expensive and requires additional hardware by Sundar Baglamas T [2]
It is a technique that uses gloves and several hand sensors to recognize different hand gestures. The sensors have motion detectors that are costly, and it makes the hand hard to move because of the weight by Sai Bharath Padigala Gogineni Hrushikesh MadhavSaranu Kishore Kumar [3]
It is discussed a technique using deep learning to recognize the ASL gestures with the help of a public dataset available on Kaggle. It employs several ML algorithms in the dataset and gives a classified report on the results for each ML algorithm by Sakshi Mankar Kanishka Mohapatra Mansi Talavadekar [4].
It is a technique that uses color features and contour extraction to determine rather than the different hand gestures by Mallikarjun Rao, Cheguri SowmyaP.A. Sujasri [5]
It is an approach for Realtime hand gesture recognition for human computer interaction using CNN. The drawback here is that it does not detect any sign language gestures rather it detects some hand signs that are used for Human computer Interface rather than sign language by Pei Xu [6].
It is technique Recognition of Dynamic Hand Gestures from 3D Motion Data using LSTM and CNN architectures. Published in 2017 by Chinmaya R. Naguri, Razvan C. Bunescu.[7].
It is technique Hand Gesture Tracking and Recognition based Human Computer Interaction System and Its Applications published in 2018 by Chinmaya R. Naguri, Razvan C. Bunescu [8].
A Method for Stochastic Optimization. Published as a conference paper at the 3rd International Conference for Learning Representations, San Diego, 2015 by Diederik P. Kingma, Jimmy Ba. Adam [9].
The Linguistics of American Sign Language, American National Standard for Information Sciences.by Clayton Valli, Ceil Lucas [10].
It is Hand Gesture Recognition for Human Computer Interaction. 7th International Conference on Advances in Computing Communications, ICACC- 2017, 22–24 August 2017, Cochin, India by Aashni Hariaa, Archanasri Subramaniana, Nivedhitha Asokkumara, Shristi Poddara, Jyothi S Nayaka,[11]
It is Hand Gesture Detection for American Sign Language using K- Nearest Neighbor with Media pipe by Arsheldy Alvin1, Nabila Husna Shabrina2, Aurelius Ryo3, Edgar Christian4 Fakultas Teknik dan Informatika, Universitas Multimedia Nusan- Tara, Teknik Komputer Tangerang [12]
A Real- time Hand Gesture Recognition and Human- Computer Interaction System by Pei Xu Department of Electrical and Computer Engineering, University of Minnesota, Twin Cities [13]
A Google Re- search 1600 Amphitheatre Pkwy, Mountain View, CA 94043, USA by Fan Zhang ,Valentin Bazarevsky ,Andrey Vakunov ,Andrei Tkachenka ,George Sung, Chuo Ling Chang,Matthias Grundmann [14]
Hand gesture recognition using machine learning algorithms. Computer Science and Information Technologies by Abhishek B, Kanya Krishi, Meghana M, Mohammed Daaniyaal, Anupama HS, BMS Institute of Technology, Bangalore, India.[15]
The Hand gesture recognition is based on convolution neural network. part of Springer Nature 2017 by Gongfa Li, · Heng Tang, · Ying Sun, · Jianyi Kong, · Guozhang Jiang, · D u Jiang · Bo Tao, ·Shuang Xu, · Honghai Liu.[16].
The Dynamic Hand Gesture Recognition Using 3DCNN and LSTM with FSM Context-Aware Model by Noorkholis Luthfil Hakim, Timothy K. Shih, Sandeli Priyanwada Kasthuri Arachchi ,Wisnu Aditya, Yi-Cheng Chen and Chih-Yang Lin [17].