An efficient cloud based image target recognition SDK for mobile applications

Haslina Arshad, Lam Meng Chun, Waqas Khalid Obeidy, Tan Siok Yee

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable especially when these devices try to access the shared pool of computing resources provided by the cloud, on demand. Mobile services such as image target recognition SDK may enrich their functionality by delegating heavy tasks to the clouds as the remote processing. This paper proposes an image target recognition SDK based on cloud with the main goal of lightweight implementation on mobile devices based on processing performed over the cloud. In such circumstances, the focus of the proposed image target recognition SDK needs to be on effectiveness, robustness, and simplicity, while still preserving a high level of functionality (i.e. good recognition). Application areas involve android library development, pattern recognition, and web portal development. The applications mentioned in this paper bring an added value by being success stories for mobile cloud computing domain in general.

Original languageEnglish
Pages (from-to)496-502
Number of pages7
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Volume7
Issue number2
DOIs
Publication statusPublished - 2017

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Mobile Applications
value added
Mobile cloud computing
Equipment and Supplies
Smartphones
Processing
Mobile devices
Libraries
Pattern recognition
Cloud Computing
Smartphone

Keywords

  • Cloud computing
  • Feature extraction
  • Image recognition
  • Mobile application

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Computer Science(all)
  • Engineering(all)

Cite this

An efficient cloud based image target recognition SDK for mobile applications. / Arshad, Haslina; Meng Chun, Lam; Obeidy, Waqas Khalid; Yee, Tan Siok.

In: International Journal on Advanced Science, Engineering and Information Technology, Vol. 7, No. 2, 2017, p. 496-502.

Research output: Contribution to journalArticle

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