A sign language to text converter using leap motion

Fazlur Rahman Khan, Huey Fang Ong, Nurhidayah Bahar

Research output: Contribution to journalArticleResearchpeer-review

16 Citations (Scopus)


This paper presents a prototype that can convert sign language into text. A Leap Motion controller was utilised as an interface for hand motion tracking without the need of wearing any external instruments. Three recognition techniques were employed to measure the performance of the prototype, namely the Geometric Template Matching, Artificial Neural Network and Cross Correlation. 26 alphabets from American Sign Language were chosen for training and testing the proposed prototype. The experimental results showed that Geometric Template Matching achieved the highest recognition accuracy compared to the other recognition techniques.

Original languageEnglish
Pages (from-to)1089-1095
Number of pages7
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Issue number6
Publication statusPublished - 2016
Externally publishedYes


  • American sign language
  • Artificial neural network
  • Cross correlation
  • Geometric template matching
  • Leap motion
  • Sign language to text

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