Abstract
Sign language is a language formed by a combination of finger, hand, body movements and facial expressions used by persons with disabilities such as deaf and speech impaired. One of these sign language recognitions is recognition using Leap Motion Controller (LMC) sensor technology. In addition to the sign language that is formed has diversity such as folded fingers, hidden fingers, indonesian sign forms also have characteristics and shapes that are almost similar to one another. The LMC sensor is not always able to recognize all forms of signs properly. In this study, optimization is proposed at the feature level where optimization aims to provide more detailed features and characteristics of each sign language formed. The stages of the process are designing the layout of the sensors, adding features and combining feature data from each sensor. The test of the feature optimization on this dual LMC sensor can provide an increase in the recognition accuracy of the given Indonesian sign language. The Indonesian sign language can be recognized well with an average accuracy of 87.24% and the optimization carried out is able to produce an increase in accuracy of up to 2.88%.
Highlights
Sign language is a language formed by a combination of finger movements, orientation of hand, arm, body movements as well as lip movements and facial expressions.Sign language communication in Indonesia is one of the sign language communications built by adopting the American Sign Language (ASL) sign language which is owned by America.Communication between persons with disabilities will certainly be very difficult for normal people to understand in general and will find it difficult to know and understand the sign language conveyed by the deaf and speech impaired.This is due to differences in methods and ways of communication, and vice versa
The results obtained will be compared between scenarios so that the best scenario can be obtained in optimizing recognize for Indonesian sign language
With the addition of features made previously, it can optimize the recognition of sensors for Indonesian Sign Language
Summary
Sign language is a language formed by a combination of finger movements, orientation of hand, arm, body movements as well as lip movements and facial expressions.Sign language communication in Indonesia is one of the sign language communications built by adopting the American Sign Language (ASL) sign language which is owned by America.Communication between persons with disabilities will certainly be very difficult for normal people to understand in general and will find it difficult to know and understand the sign language conveyed by the deaf and speech impaired.This is due to differences in methods and ways of communication, and vice versa. We need a system that can translate the difference in communication methods between sign language communication and normal communication. In the field of technology, during the last decade many studies have been carried out and some of these sign language recognition studies have focused on the algorithms used or methods consisting of static and dynamic cues [1]. Many research works have been directed and carried out to develop the recognition of different sign languages [2]. Some of these studies are American Sign Language(ASL) [3], Malaysian Sign Language [4], Indian Sign Language (ISL) [5] and Arabic Sign Language (ArSL) [6]. Other sign language research uses an image-based and sensor-based
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