Real time static hand gesture recognition system prototype for Indonesian sign language

Author(s):  
Rudy Hartanto ◽  
Adhi Susanto ◽  
Paulus Insap Santosa
2021 ◽  
Author(s):  
Saliya S Shaikh ◽  
Akram A Patel ◽  
Pravadha Deshmukh Pawar ◽  
Rubana P Shaikh

Too many research has been done in the field of Human Computer Interaction (HCI). One of the system called Hand Gesture Recognition (HGR) gives solution to build the HCI systems. Now a days, computer is used as a interpreter between humans. The proposed system is used to recognize the real time static hand gesture of Indian sign language number system zero to nine. In this paper we propose a system for hand gesture recognition which is simple and fast. Based on the proposed algorithm, this system can automatically convert the input hand gesture into the text and audio. The system first capture the image of hand gesture shown by user using a simple webcam then using our proposed algorithm it recognize the gesture. This system can use for real time application due to the use of simple logic condition applied to recognize the gesture. The proposed system is size invariant and implemented using OpenCV.


The aim is to present a real time system for hand gesture recognition on the basis of detection of some meaningful shape based feature like orientation, center of mass, status of fingers in term of raised or folded fingers of hand and their respective location in image. Hand gesture Recognition System has various real time applications in natural, innovative, user friendly way of how to interact with the computer which has more facilities that are familiar to us. Gesture recognition has a wide area of application including Human machine interaction, sign language, game technology robotics etc are some of the areas where Gesture recognition can be applied. More specifically hand gesture is used as a signal or input means given to the computer especially by disabled person. Being an interesting part of the human and computer interaction hand gesture recognition is needed for real life application, but complex of structures presents in human hand has a lot of challenges for being tracked and extracted. Making use of computer vision algorithms and gesture recognition techniques will result in developing low-cost interface devices using hand gestures for interacting with objects in virtual environment. SVM (support vector machine) and efficient feature extraction technique is presented for hand gesture recognition. This method deals with the dynamic aspects of hand gesture recognition system.


2012 ◽  
Vol 6 ◽  
pp. 98-107 ◽  
Author(s):  
Amit Gupta ◽  
Vijay Kumar Sehrawat ◽  
Mamta Khosla

2021 ◽  
Vol 102 ◽  
pp. 04009
Author(s):  
Naoto Ageishi ◽  
Fukuchi Tomohide ◽  
Abderazek Ben Abdallah

Hand gestures are a kind of nonverbal communication in which visible bodily actions are used to communicate important messages. Recently, hand gesture recognition has received significant attention from the research community for various applications, including advanced driver assistance systems, prosthetic, and robotic control. Therefore, accurate and fast classification of hand gesture is required. In this research, we created a deep neural network as the first step to develop a real-time camera-only hand gesture recognition system without electroencephalogram (EEG) signals. We present the system software architecture in a fair amount of details. The proposed system was able to recognize hand signs with an accuracy of 97.31%.


Author(s):  
Joseph C. Tsai ◽  
Shih Ming Chang ◽  
Shwu Huey Yen ◽  
Kuan Ching Li ◽  
Yung Hui Chen ◽  
...  

2013 ◽  
Vol 8 (11) ◽  
pp. 185-193 ◽  
Author(s):  
Jiali Li ◽  
Lingxiang Zheng ◽  
Yuqi Chen ◽  
Yixiong Zhang ◽  
Peng Lu

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