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Autofocus window selection algorithm based on saliency detection
Author(s): Guang Chen; Xuewu Fan
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Paper Abstract

Focus window selection is a very important step in the process of Auto-Focusing(AF). This paper proposes a new method for the selection of focus window, where a fast AF window selection algorithm based on image saliency region extraction is used to cut down the computation time and overcome the disturbance of the background in the automatic focusing system. Firstly, the salient object detection method based on the Minimum Barrier Plus(MB+) Transform algorithm is utilized to calculate the salient regions of the image in order to obtain a feature map. Secondly, a threshold method is used to de-noise the feature map. Then, correlation treatment method and boundary expansion method are used to build the focus window, of which the size and position are self-adaptive with the target. To the end, in this study, a comparison is made between the commonly used algorithm and the introduced window selection algorithm based on the improved MB + saliency detection in terms of accuracy and computation time. The result obtained indicates that our algorithm has better performance in highlighting the potential focus targets. And its better accuracy and less computation time make it suitable for tasks in general scenes and complex backgrounds.

Paper Details

Date Published: 24 July 2018
PDF: 7 pages
Proc. SPIE 10827, Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018), 108271J (24 July 2018); doi: 10.1117/12.2500193
Show Author Affiliations
Guang Chen, Xi'an Institute of Optics and Precision Mechanics, CAS (China)
Univ. of Chinese Academy of Sciences (China)
Xuewu Fan, Xi'an Institute of Optics and Precision Mechanics, CAS (China)


Published in SPIE Proceedings Vol. 10827:
Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)
Yingjie Yu; Chao Zuo; Kemao Qian, Editor(s)

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