• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3086-3103
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• 2017

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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.288-291
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• 2011

Video stabilization is an important image enhancement widely used in surveillance system in order to improve recognition performance. Most previous methods calculate inter-frame homography to estimate global motion. These methods are relatively slow and suffer from significant depth variations or multiple moving object. In this paper, we propose a fast and practical approach for video stabilization that selects the most reliable key frame as a reference frame to a current frame. We use optical flow to estimate global motion within an adaptively selected region of interest in static camera environment. Optimal global motion is found by probabilistic voting in the space of optical flow. Experiments show that our method can perform real-time video stabilization validated by stabilized images and remarkable reduction of mean color difference between stabilized frames.

• Transactions of the Society of Information Storage Systems
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• v.6 no.2
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• pp.74-78
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• 2010

In this paper, 2-axis driving mechanism, which uses voice coil motor (VCM), is proposed to measure the friction force. The proposed VCM actuator consists of two parts; structural part and magnetic circuit part. Structural part is simplified to perform the friction experiments. Magnetic circuit part is composed of two parts. The experiments are accomplished by changing the mass of moving part. Through the experiments, optimal dimension is selected. Finally, the experimental results are verified and the optimal case is applied to the 2-axis driving mechanism, optical image stabilization actuator.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.115-127
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• 2023

Video stabilization is one of the camera technologies that the importance is gradually increasing as the personal media market has recently become huge. For deep learning-based video stabilization, existing methods collect pairs of video datas before and after stabilization, but it takes a lot of time and effort to create synchronized datas. Recently, to solve this problem, unsupervised learning method using only unstable video data has been proposed. In this paper, we propose a network structure that learns the stabilized trajectory only with the unstable video image without the pair of unstable and stable video pair using the Convolutional Auto Encoder structure, one of the unsupervised learning methods. Optical flow data is used as network input and output, and optical flow data was mapped into grid units to simplify the network and minimize noise. In addition, to generate a stabilized trajectory with an unsupervised learning method, we define the loss function that smoothing the input optical flow data. And through comparison of the results, we confirmed that the network is learned as intended by the loss function.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.265-271
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• 2015

In this study, optical design for small satellite camera equipped with online optical compensation movements has been conducted. Satellite camera equipped with compensation movements at M2 mirror and focal plane can guarantee the MTF performance through the focal plane image stabilization and the on-orbit optical alignment. The designed optical system is schmidt-cassegrain type that has M1 mirror of a diameter 200mm, GSD 3.8m at an altitude of 700km, and 50 % MTF performance. The performance of the designed optical system has been analyzed through the method of ray aberration curve, spot diagram, and MTF. It has been found by the optical performance analysis that the designed optical system satisfies the optical requirements of satellite camera equipped with online optical compensation movements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.472-478
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• 2015

This paper describes the design of the active optical compensation movements(at focal plane, secondary mirror) for the image stabilization of a small satellite camera. The movements can correct optical misalignment on-line and directly compensate vibration disturbances in the focal plane. Since the devices are installed inside the space camera, it has an remarkable advantage to deal with the structural deformation of a space camera effectively. In this paper, the requirements of the active optical compensation movements for 1m GSD small satellite camera have been analyzed. Based on the established requirements, the design of the active compensation movements have been conducted. The designed active optical compensation system can control 5 axes movements independently to compensate micro-vibration disturbances in the focal plane and to refocus the optical misaligned satellite camera.

• Transactions of the Society of Information Storage Systems
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• v.7 no.2
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• pp.70-74
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• 2011

The mobile camera module is a device to be inserted in the digital device for camera feature. The mobile camera module is being shaken by vibrations such as handshake during the exposure time. The clarity is compromised by these vibrations, thus the vibration is considered as an external disturbance. Moreover the use of mobile camera module has been being expanded for automotive vibration should be considered. These external disturbances can cause image blurring, thus optical image stabilization should be applied for image compensation. The compensator is fulfilled mechanically by movable lens group or image sensor that adjusts the optical path to the camera movement. Open loop control is useful for well-defined systems like compliant mechanism. Notch filter and lead compensator are designed and applied to improve the stability and bandwidth. The final level of image compensating is confirmed by image processing with MATLAB and CODE V to verify the better performance.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.254.1-254.1
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• 2007

• Journal of the Semiconductor & Display Technology
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• v.13 no.1
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• pp.27-33
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• 2014

Video from unmanned aerial vehicle (UAV) is influenced by natural environments due to the light-weight UAV, specifically by winds. Thus UAV's shaking movements make the video shaking. Objective of this paper is making a stabilized video by removing shakiness of video acquired by UAV. Stabilizer estimates camera's motion from calculation of optical flow between two successive frames. Estimated camera's movements have intended movements as well as unintended movements of shaking. Unintended movements are eliminated by smoothing process. Experimental results showed that our proposed method performs almost as good as the other off-line based stabilizer. However estimation of camera's movements, i.e., calculation of optical flow, becomes a bottleneck to the real-time stabilization. To solve this problem, we make parallel stabilizer making average 30 frames per second of stabilized video. Our proposed method can be used for the video acquired by UAV and also for the shaking video from non-professional users. The proposed method can also be used in any other fields which require object tracking, or accurate image analysis/representation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1395-1400
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• 2018

EO TGP(Electro-Optical Targeting Pod) is an optical tracking system which has various functions such as target tracking and image stabilization and LOS(Line of Sight) change. Especially, it is very important to move the LOS into a interest point for joystick command. When pilot move joystick in order to observe different scene, EO TGP gimbals should be operated properly. Generally, most EOTS just operate corresponding gimbal for joystick command. For example, if pilot input horizontal command in order to observe right hand screen, it just drive azimuth gimbal at any position. But in the screen, the image dosen't move in a horizontal direction because gimbal structure is Euler angle. And image rotation is occurred by elevation gimbal angle. So we need to move Pitch gimbal. So in the paper, we designed LOS moving algorithm which convert LOS command to gimbal velocity command to move LOS properly. We modeled a differential kinematic equation and then change the joystick command into velocity command of gimbals. This algorithm generate velocity command of each gimbal for same horizontal direction command. Finally, we verified performance through MATLAB/Simulink.