Measurement of sinusoidal vibration from motion blurred images

  • Authors:
  • Shigang Wang;Baiqing Guan;Guobao Wang;Qian Li

  • Affiliations:
  • School of Mechanical Engineering, Institute of Mechatronics and Automation Technology, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, PR China;School of Mechanical Engineering, Institute of Mechatronics and Automation Technology, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, PR China;School of Mechanical Engineering, Institute of Mechatronics and Automation Technology, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, PR China;School of Mechanical Engineering, Institute of Mechatronics and Automation Technology, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai 200030, PR China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2007

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Abstract

Previous vision-based methods usually measure vibration from large sequence of unblurred images recorded by high-speed video or stroboscopic photography. In this paper, we propose a novel method for sinusoidal vibration measurement based on motion blurred images. We represent the motion blur information in images by the relationship between the geometric moments of the motion blurred images and the motion, and estimate the vibration parameters from this motion blur cue. We need only one motion blurred image and an unblurred image or two successive frames of blurred images to calculate the parameters of low-frequency vibration as well as the amplitude and direction of high-frequency vibration, while unblurred-image-based techniques rely on much more images to obtain the same results and existing motion-blurred-image-based approaches only estimate the amplitude of high-frequency vibration. Experimental results with both simulated and real vibrations of low and high frequencies are employed to demonstrate the effectiveness of the proposed scheme.