An auto focus framework for computer vision systems

Nijad Anabtawi; Rony M. Ferzli

doi:10.1117/12.2083571

27 February 2015 An auto focus framework for computer vision systems

Nijad Anabtawi, Rony M. Ferzli

Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 94050W (2015) https://doi.org/10.1117/12.2083571
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Nijad Anabtawi and Rony M. Ferzli "An auto focus framework for computer vision systems", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050W (27 February 2015); https://doi.org/10.1117/12.2083571

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