A novel training based auto-focus for mobile-phone cameras

Jong Woo Han, Jun Hyung Kim, Hyo Tae Lee, Sung Jea Ko

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


In this paper, we propose a fast and accurate training based auto-focus (AF) method for mobile-phone cameras. Given a set of training data, the proposed method collects feature vectors consisting of focus value increment ratio. The representative feature vectors corresponding to every possible best in-focus lens position (BILP) are stored in the database. In the proposed training based AF method, the BILP is obtained by comparing the input feature vector with the representative feature vectors in the database. To further enhance the accuracy of the proposed AF method, we also introduce a new focusing window that is effective in detecting the target object. The experimental results show that the proposed method can accurately estimate the BILP faster than the existing methods.

Original languageEnglish
Article number5735507
Pages (from-to)232-238
Number of pages7
JournalIEEE Transactions on Consumer Electronics
Issue number1
Publication statusPublished - 2011 Feb

Bibliographical note

Funding Information:
1This research was supported by a Korea University Grant and by Mid-career Researcher Program through National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0000449).


  • Autofocus
  • feature vector
  • focus value
  • focusing window
  • mobile-phone cameras

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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