Dynamics-based motion de-blurring for a PZT-driven, compliant camera orientation mechanism

Kim, Michael D.; Ueda, Jun

doi:10.1177/0278364914557968

Cited by 17 publications

(8 citation statements)

References 46 publications

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“…The motion blur will lead to significant systematic errors and incomplete measurement data because the target seeking process may not give exact detection. In recent years, research efforts have been devoted to the development of deblurring and denoising algorithms and blur image analysis methods [62][63][64]. Wang et al [65] proposed a method for vibration measurement based on the blurred images with the aid of the relationship between the geometric moments of the unblurred and blurred motion.…”

Section: Systematic Errors Assessment Andmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

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In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.

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Section: Systematic Errors Assessment Andmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

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“…It was modeled experimentally by the observation of a step response and linearity of the system was verified in [15], [9]. Figure 4 shows the time response of the camera positioner system driven by cellular actuators given a step command.…”

Section: Cellular Actuatorsmentioning

confidence: 99%

Discrete switching commands for tracking and vibration suppression using a quantized, compliant camera orientation system

Kim

Ueda

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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This paper presents a method to generate discrete switching commands for a camera orientation system exhibiting quantization and flexibility to achieve smooth-pursuit like movements. Existing vibration suppression techniques and camera positioning devices have shown notable results but focused only on point-to-point movements. A desired motion profile can be generated by incorporating a classical feedback controller with PWM quantization but each unit actuator is required to produce high-frequency switching that can potentially damage the complaint mechanism. The proposed controller generates pulse-like switching commands for smooth-pursuit like motion to match the velocity of an object of interest. Then, switching commands for vibration suppression are generated to avoid high-frequency switching. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuator. The experiment results show that the camera orientation system successfully achieved dynamic vision given the proposed commands in an open-loop manner.

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“…The program of Xu etal. was the only open source with GPU capability and was reported as the fastest method among image-based methods [18].…”

Section: A Computation Time Of De-blurringmentioning

confidence: 99%

Real-time image de-blurring and image processing for a robotic vision system

Kim

Ueda

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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This paper proposes a method for real-time deblurring of images captured by a robotic system. De-blurring is achieved by combining a dynamics-based approach and parallel computing. Existing methods have successfully restored a blurry image but were not suitable for real-time applications. The dynamics-based method with parallel programming in the FPGA is used to estimate the PSF during the camera exposure window. The deconvolution process, which involves iterative matrix calculations with millions of pixels, is then performed on the GPU to achieve real-time performance. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuators and one vision sensor. The frame rate of image de-blurring ranges from 20.32 to 40.68 fps and thus real-time performance is achieved. In comparison to existing methods, the proposed method produces the best image quality. The dynamics-based approach is extended to real-time image stitching which is computationally cheap and robust to motion blur. It is demonstrated from image stitching that real-time de-blurring is beneficial for image processing.

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Dynamics-based motion de-blurring for a PZT-driven, compliant camera orientation mechanism

Cited by 17 publications

References 46 publications

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

Discrete switching commands for tracking and vibration suppression using a quantized, compliant camera orientation system

Real-time image de-blurring and image processing for a robotic vision system

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