Arabic sign language recognition using Ada-Boosting based on a leap motion controller
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ORIGINAL RESEARCH
Arabic sign language recognition using Ada-Boosting based on a leap motion controller Basma Hisham1
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Alaa Hamouda1
Received: 5 September 2018 / Accepted: 26 September 2020 Bharati Vidyapeeth’s Institute of Computer Applications and Management 2020
Abstract According to the World Health Organization (WHO), 466 million people are suffering from hearing loss, i.e., 5% of the world population, of which 432 million (93%) are adults and 34 million (17%) children. The main problem is how deaf and hearing-impaired communicate with people and each other, how they get education or do their daily activities. Sign language is the main communication method for them. Building automatic hand gestures recognition system has many challenges specially in Arabic. Solving recognition problem and practically develop real-time recognition system is another challenge. Several types of research have been conducted on sign language recognition systems but for Arabic Sign Language are very limited. In this paper, an Arabic Sign Language (ArSL) recognition system that uses a Leap Motion Controller and Latte Panda is introduced. The recognition phase depends on two machine learning algorithms: (a) KNN (k-Nearest Neighbor) and (b) SVM (Support Vector Machine). Afterwards, an Ada-Boosting technique is applied to enhance the accuracy of both algorithms. A direct matching technique, DTW (Dynamic Time Wrapping), is applied and compared with AdaBoost. The proposed system is applied on 30 hand gestures which are composed of 20 single-hand gestures and 10 doublehand gestures. The experimental results show that the DTW achieved an accuracy of 88% for single-hand gestures and 86% for double-hand gestures. Overall, the & Basma Hisham [email protected] Alaa Hamouda [email protected] 1
Computers and Systems Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt
proposed model’s recognition rate reached 92.3% for single-hand gestures and 93% for double-hand gestures after applying the Ada-Boosting. Finally, a prototype of our model was implemented in a single board (Latte Panda) to increase the system’s reliability and mobility. Keywords ArSL KNN SVM DTW Ada-Boosting Latte Panda
1 Introduction Sign language is the most expressive way for deaf people to communicate and interact with others. It can be defined as ‘‘The language that uses the manual representation and the motion and orientation of body parts such as hands, arms, wrist, etc., in addition to the facial expressions to represents the signer’s concepts and thoughts’’ [1]. It is the most popular way of communication in the deaf and hearing-impaired communities, also it is the natural way of communication between them and normal people. There is a lack of awareness of the language with a portion of members of deaf societies and this led to challenges to its learning and academic processes, difficulties in integration, and limitation in communication with others especially the hearing people as well as benefiting from services. Th
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