• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.1-11
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• 2008

This paper proposes a real-time method using a 3-axis accelerometer to enhance blurred images taken from a camera loaded in mobile devices. Blurring phenomenon is a smoothing effect occurring in photo images. Algorithms to cope with blurring phenomenon is essential since small-size mobile devices tremble severely by even a tiny hand-shaking of a user. In this paper, accurate sensing characteristics of the 3-axis accelerometer is acquired by applying the sensor in pendulum motion and the blurring phenomenon is modeled as a uniform distribution and Gaussian distribution. Also, non-Gaussian distributed model is observed in the experiment of real blurring phenomenon and a particular deblurring function is designed by reversing the model. It has been demonstrated that the application of trembling information to the deblurring function adequately removes the blurring phenomenon.

• Transactions of the Society of Information Storage Systems
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• v.5 no.1
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• pp.8-13
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• 2009

In this study, to compensate trembling of camera caused by vibration of user's hand, 2-axis voice coil actuator of optical image stabilizer (OIS) is suggested. In consideration of actuating performance, volume of OIS and application of hall sensor, one of concept models is selected and it is optimized to maximize the actuating performance. Two types of mechanisms that have the feasibility of moving in 2-axis and the capability of including the optimized EM circuit are proposed. Finally both types are fabricated and then actuating performance of OIS actuator and behavior of hall sensor are verified through the experiment.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.124-133
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• 1999

In this paper, an event detection algorithm is proposed based on the statistics of subblock images. For an event of small size, we first divide each image into smaller subblocks and then for camera trembling, we use the statistics of three kinds of images such as the input image, reference image, and their difference image as features of the event. Simulation results show that the proposed algorithm is much more effective in event detection than the conventional cases based on only the difference image.