Implementation of Real-Time Static Hand Gesture Recognition Using Artificial Neural Network

Lita Yusnita • Rosalina Rosalina • Rusdianto Roestam • R. B. Wahyu
Journal article Communication and Information Technology Journal • 2017 Indonesia

Abstrak

This paper implements static hand gesture recognition in recognizing the alphabetical sign from “A” to “Z”, number from “0” to “9”, and additional punctuation mark such as “Period”, “Question Mark”, and “Space” in Sistem Isyarat Bahasa Indonesia (SIBI). Hand gestures are obtained by evaluating the contourrepresentation from image segmentation of the glove wore by user. Then, it is classified using Artificial Neural Network (ANN) based on the training model previously built from 100 images for each gesture. The accuracy rate of hand gesture translation is calculated to be 90%. Moreover, speech translation recognizes NATO phonetic letter as the speech input for translation.

Metrics

  • 230 kali dilihat
  • 76 kali diunduh

Jurnal

Communication and Information Technology Journal

Communication and Information Technology Journal (CommIT) focuses on various issues spanning sof... tampilkan semua