• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Antiblurry Dejitter Image Stabilization Method of Fuzzy Video for Driving Recorders


Abstract

Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.


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Cite this article

[IEEE Style]
Jing-Ying Xiong, Ming Dai, Chun-Lei Zhao and Ruo-Qiu Wang, "Antiblurry Dejitter Image Stabilization Method of Fuzzy Video for Driving Recorders," KSII Transactions on Internet and Information Systems, vol. 11, no. 6, pp. 3086-3103, 2017. DOI: 10.3837/tiis.2017.06.016

[ACM Style]
Xiong, J., Dai, M., Zhao, C., and Wang, R. 2017. Antiblurry Dejitter Image Stabilization Method of Fuzzy Video for Driving Recorders. KSII Transactions on Internet and Information Systems, 11, 6, (2017), 3086-3103. DOI: 10.3837/tiis.2017.06.016