Automatic Image stabilizing system by full-digital signal processing

Uomori,; Morimura,; Hirofumi,; Sakaguchi,; Kitamura,

doi:10.1109/icce.1990.665986

Cited by 11 publications

(16 citation statements)

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“…Digital image stabilization (DIS) is the process of removing the undesired motion effects to generate a compensated image sequence by using digital image processing techniques without any mechanical devices such as gyro sensors or a fluid prism [4]. The major advantages of DIS are: 1) machine independence and 2) suitability for miniature hardware implementation (since the mechanical device is not required for compensation) [5].…”

mentioning

confidence: 99%

A Robust In-Car Digital Image Stabilization Technique

Hsu

Liang

Fan

et al. 2007

IEEE Trans. Syst., Man, Cybern. C

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Machine vision is a key technology used in an intelligent transportation system (ITS) to augment human drivers' visual capabilities. For the in-car applications, additional motion components are usually induced by disturbances such as the bumpy ride of the vehicle or the steering effect, and they will affect the image interpretation processes that is required by the motion field (motion vector) detection in the image. In this paper, a novel robust in-car digital image stabilization (DIS) technique is proposed to stably remove the unwanted shaking phenomena in the image sequences captured by in-car video cameras without the influence caused by moving object (front vehicles) in the image or intentional motion of the car, etc. In the motion estimation process, the representative point matching (RPM) module combined with the inverse triangle method is used to determine and extract reliable motion vectors in plain images that lack features or contain a large low-contrast area to increase the robustness in different imaging conditions, since most of the images captured by in-car video cameras include large low-contrast sky areas. An adaptive background evaluation model is developed to deal with irregular images that contain large moving objects (front vehicles) or a low-contrast area above the skyline. In the motion compensation processing, a compensating motion vector (CMV) estimation method with an inner feedbackloop integrator is proposed to stably remove the unwanted shaking phenomena in the images without losing the effective area of the images with a constant motion condition. The proposed DIS technique was applied to the on-road captured video sequences with various irregular conditions for performance demonstrations.Index Terms-Adaptive background-based evaluation function, in-car digital image stabilizer (ICDIS), intelligent transportation system (ITS), inverse triangle method, representative point matching (RPM), smoothness index (SI).

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mentioning

confidence: 99%

A Robust In-Car Digital Image Stabilization Technique

Hsu

Liang

Fan

et al. 2007

IEEE Trans. Syst., Man, Cybern. C

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“…The block matching method, projection method, feature point method and frequency domain estimation method are used for motion estimation of image sequence [1][2][3][4]. Commonly used blockmatching method is to divide the image into several rectangular macro-blocks, solving their motion vectors and then used to estimate the global motion of the image.…”

Section: Introductionmentioning

confidence: 99%

Model Parameters Estimation for Image Motion Compensation

Zhong¹,

Li²,

Zhao³

2013

Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation

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Abstract-Fast and optimal motion estimation method is proposed for electronic image stabilization. First, an approach for macro-block judgment is presented. Before motion vectors calculation, gradient information is analyzed, only useful reference blocks that are indispensable for accurate motion estimation are selected, by which the number of macro-blocks for subsequent calculation is reduced. Second, in the block matching, an improved SSDA is used to reduce computing cost. Finally, the affine transformation model and similarity transformation model of image motion are created and using least squares method for solving the optimal estimation of model parameters. Experimental results show the accuracy and fast computing speed of the proposed method.

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“…Figure 4 shows two comparisons between the present method and the widely-used stabilization with motion dampening 1 (e.g. [5]), using an actual fifteen-seconds video. In each plot, corresponding to the vertical image translation and image rotation, respectively, there are shown the ±w f bands around the parameter measurements; the thick line indicates the stabilized trajectory using the present method whereas the thin trajectory shows the less optimal result of motion dampening.…”

Section: Solution With the Viterbi Methodsmentioning

confidence: 98%

“…Two qualitative comparisons between stabilized trajectories obtained with the present method (bold) and stabilization using motion dampening[5] (thin trajectory), both shown within the respective stabilization bands.…”

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confidence: 98%

Video stabilization as a variational problem and numerical solution with the viterbi method

Pilu¹

Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.

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This paper presents a new method for video stabilization based on a variational formulation that produces optimally stable sequences independently of the input motion but within the hard constraints imposed by finite sensor size to the maximum allowed compensatory transformation. A practical and fast numerical solution using the Viterbi algorithm is also proposed. The results show the efficacy of the method compared to a class of previous approaches.

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Automatic Image stabilizing system by full-digital signal processing

Cited by 11 publications

References 0 publications

A Robust In-Car Digital Image Stabilization Technique

A Robust In-Car Digital Image Stabilization Technique

Model Parameters Estimation for Image Motion Compensation

Video stabilization as a variational problem and numerical solution with the viterbi method

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