CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs

by Jayanth Thota, Priyanka Vangali, Xiaokun Yang
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 8
Year of Publication: 2017
Authors: Jayanth Thota, Priyanka Vangali, Xiaokun Yang
10.5120/ijca2017912853

Jayanth Thota, Priyanka Vangali, Xiaokun Yang . Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs. International Journal of Computer Applications. 158, 8 ( Jan 2017), 1-7. DOI=10.5120/ijca2017912853

@article{ 10.5120/ijca2017912853,
author = { Jayanth Thota, Priyanka Vangali, Xiaokun Yang },
title = { Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 8 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number8/26925-2017912853/ },
doi = { 10.5120/ijca2017912853 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:15.860517+05:30
%A Jayanth Thota
%A Priyanka Vangali
%A Xiaokun Yang
%T Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 8
%P 1-7
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to help physically disabled persons to make their life independent, this paper proposes an autonomous eye controlled system (AECS) on wheelchairs. In this work, several OpenCV image processing algorithms are employed to track the eye motion to coordinate the wheelchair moving left, right, and straight forward. We use the Raspberry-Pi B+ board as the system center to process the images and control the motors via GPIO. Experimental results show that the ACES system can be effectively used in the prototype, and outperforms the hand gesture controlled system by 25% processing latency reduction.

References
  1. A. Ahamed, A.U. Ahad, H.A. Sohag, and M. Ahmad. Development of low cost wireless biosignal acquisition system for ecg, emg and eog. 2015 2nd International Conference on Electrical Information and Communication Technologies (EICT2015), December 2015.
  2. C. Aruna, A. Dhivya Parameswari, M. Malini, and G. Gopu. Voice recognition and touch screen control based wheel chair for paraplegic persons. 2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE2014), March 2014.
  3. P. Britto, J. Indumathi, S. Sivarasu, and L. Mathew. Automation of wheelchair using ultrasonic and body kinematics. National Conference on Computational Instrumentation (NCCI2010), pages 19–20, March 2010.
  4. A. Dev, H.C. Chacko, and R. Varghese. Eye controlled wheel chair using eog. International Conference on Computing and Control Engineering (ICCCE 2012),, April 2012.
  5. M.A. Devi, R. Sharmila, and V. Saranya. Hybrid brain computer interface in wheelchair using voice recognition sensors. 2014 International Conference on Computer Communication and Informatics (ICCCI2014), Janauary 2014.
  6. E.S. Gedraite and M. Hadad. Investigation on the effect of a gaussian blur in image filtering and segmentation. 53rd International Symposium ELMAR-2011, pages 393 – 396, September 2011.
  7. S.U. Kumar and V.M. Vinod. Eog based wheelchair control for quadriplegics. 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS2015), March 2015.
  8. Y. Li, X. Xu, N. Mu, and L. Chen. Eye-gaze tracking system by haar cascade classifier. 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA2016), June 2016.
  9. P. Melin, C.I. Gonzalez, J.R. Castro, O. Mendoza, and O. Castillo. Edge-detection method for image processing based on generalized type-2 fuzzy logic. IEEE Transactions on Fuzzy Systems, 22(6):1515–1525, January 2014.
  10. S.D. Mhaske and M.P. Dale. Hand gesture controlled wheelchair system using image processing. International Journal of Electrical, Electronics and Computer Systems, 4(2):2347–2820, February 2016.
  11. OpenCV. Open source computer vision. http://opencv.org/.
  12. M. Rezaei, H.Z. Nafchi, and S.Morales. Global haar-like features: A new extension of classic haar features for efficient face detection in noisy images. 6th Pacific-Rim Symposium on Image and Video Technology (PSIVT 2013), 8333:302–313, 2013.
  13. M.F. Ruzaij, S. Neubert, N. Stoll, and K. Thurow. Design and testing of low cost three-modes of operation voice controller for wheelchairs and rehabilitation robotics. 2015 IEEE 9th International Symposium on Intelligent Signal Processing Proceedings (WISP2015), May 2015.
  14. K.S. Sabarish and A.M. Suman. Eyeball and blink controlled robot with fuzzy logic based obstacle avoidance system for disabled. International Conference on Electrical and Electronics Engineering (ICEEE2012), pages 16 – 17, June 2012.
  15. Y.G. Shin, K.A. Choi, S.T. Kim, and S.J. Ko. A novel single ir light based gaze estimation method using virtual glints. IEEE Transactions on Consumer Electronics, 61(2):254–260, July 2015.
  16. X. Yang and J. Andrian. A low-cost and high-performance embedded system architecture and an evaluation methodology. 2014 IEEE Computer Society Annual Symposium on VLSI (ISVLSI2014), pages 240–243, March 2014.
  17. X. Yang and J. Andrian. A novel bus transfer mode: Block transfer and a performance evaluation methodology. Integration, the VLSI Journal, 52(C):23–33, January 2016.
  18. X. Yang, X. Niu, J. Fan, and C. Choi. Mixed-signal systemon- chip (soc) verification based on system verilog model. The 45th Southeastern Symposium on System Theory (SSST 2013), pages 17–21, March 2013 2013.
  19. Bing Z. Using vector quantization of hough transform for circle detection. 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA2015), pages 393 – 396, December 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Eye controlled system gesture controlled system image processing OpenCV Raspberry-Pi

Powered by PhDFocusTM