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Proceedings Paper

An auto focus framework for computer vision systems
Author(s): Nijad Anabtawi; Rony M. Ferzli
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Paper Abstract

Capturing a clean video from a source camera is crucial for accurate results of a computer vision system. In particular, blurry images can considerably affect the detection, tracking and pattern matching algorithms. This paper presents a framework to apply quality control by monitoring captured video with the ability to detect whether the camera is out of focus or not, thus identifying blurry defective images and providing a feedback channel to the camera to adjust the focal length. The framework relies on the use of a no reference objective quality metric for the loopback channel to adjust the camera focus. The experimental results show how the framework enables reduction of unnecessary computations and thus enabling a more power efficient cameras.

Paper Details

Date Published: 27 February 2015
PDF: 7 pages
Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050W (27 February 2015); doi: 10.1117/12.2083571
Show Author Affiliations
Nijad Anabtawi, Arizona State Univ. (United States)
Rony M. Ferzli, Arizona State Univ. (United States)

Published in SPIE Proceedings Vol. 9405:
Image Processing: Machine Vision Applications VIII
Edmund Y. Lam; Kurt S. Niel, Editor(s)

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