AraMedReader: An Arabic Medicine Identifier Using Barcodes

  • Norah I. Al-Quwayfili
  • Hend S. Al-Khalifa
Part of the Communications in Computer and Information Science book series (CCIS, volume 435)


AraMedScanner is a prototype application that mainly helps the visually impaired to identify medicines by scanning their barcode and retrieving their information from a medical database. This paper presents an overview of AraMedScanner’s features and shows preliminary evaluations conducted with blind people. The results of the evaluations revealed the application limitations and leaded to new future improvements.


Medicine Identification Barcode Mobile computing Assistive Technology Visually Impaired 


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  1. 1.
    Al-Hamid, N.: Nearly 1 million in KSA are visually impaired” Arab News, (accessed: September 30, 2013)
  2. 2.
    Erin, B., Meredith, R.M., Yu, Z., Samuel, W., Jeffrey, P.B.: Visual challenges in the everyday lives of blind people. In: CHI 2013 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2117–2126 (2013)Google Scholar
  3. 3.
    Lanigan, P.E., Paulos, A.M., Williams, A.W., Rossi, D., Narasimhan, P.: Trinetra: Assistive Technologies for Grocery Shopping for the Blind. In: 2006 10th IEEE International Symposium on Wearable Computers, Montreux, pp. 147–148 (2006)Google Scholar
  4. 4.
    López-de-Ipiña, D., Lorido, T., López, U.: BlindShopping: Enabling Accessible Shopping forVisually Impaired People through Mobile Technologies. In: The 9th International Conference on Smart Homes and Health Telematics, Montreal, Canada, pp. 266–270 (2011)Google Scholar
  5. 5.
    Tekin, E., Coughlan, J.M.: A Mobile Phone Application Enabling Visually Impaired Users to Find and Read Product Barcodes. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010, Part II. LNCS, vol. 6180, pp. 290–295. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Winlock, T., Christiansen, E., Belongie, S.: Toward real-time grocery detection for the visually impaired. In: The Computer Vision Applications for the Visually Impaired Workshop (CVAVI), San Francisco (2010)Google Scholar
  7. 7.
    Chincha, R., Tian, Y.: Finding objects for blind people based on SURF features. In: BIBM Workshops: IEEE, pp. 526–527 (2011)Google Scholar
  8. 8.
    Németh, G., Olaszy, G., Bartalis, M., Kiss, G., Zainkó, C., Mihajlik, P., Haraszti, C.: Automated Drug Information System for Aged and Visually Impaired Persons. In: Miesenberger, K., Klaus, J., Zagler, W.L., Karshmer, A.I. (eds.) ICCHP 2008. LNCS, vol. 5105, pp. 238–241. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Benjamim, X.C., Gomes, R.B., Burlamaqui, A.M.F., Gonçalves, L.M.G.: Visual identification of medicine boxes using features matching. Paper presented at the meeting of the VECIMS (2012)Google Scholar
  10. 10.
    Barcode Scanner Scandit SDK, (accessed: September 29, 2013)
  11. 11.
    Saudi Food and Drug Authority, (accessed: October 10, 2013)
  12. 12.
    Vocalizer for NVDA, (accessed: January 24, 2014)
  13. 13.
    Dustin, A., Lourdes, M., Sri, K.: A Qualitative Study to Support a Blind Photography Mobile Application. In: Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2013, Rhodes Island, Greece (2013)Google Scholar
  14. 14.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Norah I. Al-Quwayfili
    • 1
  • Hend S. Al-Khalifa
    • 2
  1. 1.Center of Excellence for Telecom ApplicationsKing Abdulaziz City for Science and TechnologyRiyadhSaudi Arabia
  2. 2.Information Technology Department, College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

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