Skip to content
Research Article Open access CC BY 3.0

Hand Gesture Recognition System Based on a Geometric Model and Rule Based Classifier

A.M. Riad, Hamdy K. Elminir, Samaa M. Shohieb

Current Journal of Applied Science and Technology · pp. 1432–1444 · Published 3 Feb 2014

10.9734/BJAST/2014/7956

Abstract

As a part of natural interfaces the sign language recognition (SLR) is considered an important area of research. Such systems are considered useful tools for assisting the deaf. For example, one of the applications of sign language recognition is transcribing notes and saving sign language presentations into digital format. Hand gesture recognition systems can also be used to control useful machines, computers, screen pointers or camera-based selection devices, like the kind used on modern ‘Smart TVs’ or console games that use the Microsoft Xbox Kinect camera. A great deal of research has been paid for this area but few ones handled the Arabic Sign Language (ArSL). This work describes an isolated SLR system that extracts geometric features from a camera for the hand gesture and builds a geometric model for the hand gesture. The rule based classifier was then used for the recognition process based on the determined geometric features of a specific gesture. The proposed model was tested on seven ArSL words. The overall recognition rate was about 95.3%.

Hand gesture recognition sign language geometric model rule based classifier deaf communication

References (24)

  1. 1 Fundamentals of digital image processing
  2. 2 Image Processing, Analysis and Machine Vision [DOI]
  3. 3 Real-time American sign language recognition using desk and wearable computer based video [DOI]
  4. 4 Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning [DOI]
  5. 5 A Framework for Recognizing the Simultaneous Aspects of American Sign Language [DOI]
  6. 6 Sign Language Spotting with a Threshold Model Based on Conditional Random Fields [DOI]
  7. 7 Robust Person-Independent Visual Sign Language Recognition [DOI]
  8. 8 Using multiple sensors for mobile sign language recognition [DOI]
  9. 9 ArSLAT: Arabic Sign Language Alphabets Translator [DOI]
  10. 10 Transition movement models for large vocabulary continuous sign language recognition [DOI]
  11. 11 Australian sign language recognition [DOI]
  12. 12 Pakistan Sign Language Recognition Using Statistical Template Matching [DOI]
  13. 13 Gesture recognition using laser-based tracking system [DOI]
  14. 14 A simple sign language recognition system based on data glove [DOI]
  15. 15 Video-based sign recognition using self-organizing subunits [DOI]
  16. 16 Enhanced Level Building Algorithm for the Movement Epenthesis Problem in Sign Language Recognition [DOI]
  17. 17 ARGo: An Architecture for Sign Language Recognition and Interpretation [DOI]
  18. 18 Real Time Large Vocabulary Continuous Sign Language Recognition Based on OP/Viterbi Algorithm [DOI]
  19. 19 Spatiotemporal gesture segmentation
  20. 20 Unsupervised Modeling of Signs Embedded in Continuous Sentences [DOI]
  21. 21 A Hybrid Sign Language Recognition System [DOI]
  22. 22 Sign language analysis and recognition: A preliminary investigation [DOI]
  23. 23 Advanced man-machine interaction : fundamentals and implementation [DOI]
  24. 24 DTW/ISODATA Algorithm and Multilayer Architecture in Sign Language Recognition with Large Vocabulary [DOI]

Cited by 6

Rule-Based Classification Based on Ant Colony Optimization: A Comprehensive Review

Sayed Kaes Maruf Hossain, Sajia Afrin Ema, Hansuk Sohn · Applied Computational Intelligence and Soft Computing · 2022

Merging Tangibles and Gamification to Teach Algorithmic Thinking to KG Children With “Gamirithmic”

Samaa Mohammed Shohieb, Ceymi Doenyas, Waleed Mohamed Al-Adrousy · Advances in Game-Based Learning · 2022

Showing 2 of 6 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

17

Page views

0

PDF downloads

1

Outbound clicks

6

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.