An improved algorithm of laser spot center detection in strong noise background

Le Zhang; Qianqian Wang; Xutai Cui; Yu Zhao; Zhong Peng

doi:10.1117/12.2286292

10 January 2018 An improved algorithm of laser spot center detection in strong noise background

Le Zhang, Qianqian Wang, Xutai Cui, Yu Zhao, Zhong Peng

Proceedings Volume 10616, 2017 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments; 106160S (2018) https://doi.org/10.1117/12.2286292
Event: International Conference on Optical Instruments and Technology 2017, 2017, Beijing, China

Abstract

Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

Citation Download Citation

Le Zhang, Qianqian Wang, Xutai Cui, Yu Zhao, and Zhong Peng "An improved algorithm of laser spot center detection in strong noise background", Proc. SPIE 10616, 2017 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 106160S (10 January 2018); https://doi.org/10.1117/12.2286292

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