Open AccessImplementation and Performance Analysis of Different Hand Gesture Recognition Methods
Author(s) -
Md. Manik Ahmed,
Md. Anwar Hossain,
A F M Zainul Abadin
Publication year - 2019
Publication title -
global journal of computer science and technology
Language(s) - English
Resource type - Journals
ISSN - 0975-4172
DOI - 10.34257/gjcstdvol19is3pg13
Subject(s) - computer science , gesture , gesture recognition , speech recognition , artificial intelligence , human–computer interaction
In recent few years, hand gesture recognition is one of the advanced grooming technologies in the era of human computer interaction and computer vision due to a wide area of application in the real world. But it is a very complicated task to recognize hand gesture easily due to gesture orientation, light condition, complex background, translation and scaling of gesture images. To remove this limitation, several research works have developed which is successfully decrease this complexity. However, the intention of this paper is proposed and compared four different hand gesture recognition system and apply some optimization technique on it which ridiculously increased the existing model accuracy and model running time. After employed the optimization tricks, the adjusted gesture recognition model accuracy was 93.21% and the run time was 224 seconds which was 2.14% and 248 seconds faster than an existing similar hand gesture recognition model. The overall achievement of this paper could be applied for smart home control, camera control, robot control, medical system, natural talk, and many other fields in computer vision and human-computer interaction.