• JSTS:Journal of Semiconductor Technology and Science
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• 제13권1호
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• pp.34-42
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• 2013

Human faces have been broadly studied in digital image and video processing fields. An appearance-based method, the adaptive boosting learning algorithm using integral image representations has been successfully employed for face detection, taking advantage of the feature extraction's low computational complexity. In this paper, we propose a face-detection postprocessing method that equalizes instantaneous facial regions in an efficient hardware architecture for use in real-time multimedia applications. The proposed system requires low hardware resources and exhibits robust performance in terms of the movements, zooming, and classification of faces. A series of experimental results obtained using video sequences collected under dynamic conditions are discussed.

• Journal of the Institute of Convergence Signal Processing
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• 제10권2호
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• pp.106-111
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• 2009

Real-time video stabilization technology is used in correction for the camera vibrations of the hand-held camera by hand or fixed camera by external condition. This paper is about the counterplan to cope with the vibration of the movie generated by the large external cause relatively. we use the movie stabilization parameters with the phase correlation method based the DFT to get the displacements of the current frame to the reference frame. we use the kalman filter for the efficient and stable searching works on the phase correlation map and present the proper conditions for the real-time processing through the experiments. We propose the measure to evaluate the capability of the video stabilizer which is the standard deviation of the brightness of the center block. and compare the capability for the video sequences randomly shifted and the jittered video sequences obtained from camera.

• Journal of the Institute of Convergence Signal Processing
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• 제10권4호
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• pp.233-238
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• 2009

In this paper, we propose the methods to select the stable region for the detect region which is required in the system used the face to the ROI in the auto-focus digital camera. this method regards the face region as the ROI in the progressive input frame and focusing the region in the mobile camera embeded ISP module automatically. The learning algorithm to detect the face is the Adaboost algorithm. we proposed the method to detect the slanted face not participate in the train process and postprocessing method for the results of detection, and then we proposed the stabilization method to sustain the region not shake for the region. we estimated the capability for the stabilization algorithm using the RMS between the trajectory and regression curve.

• Journal of the Korea Institute of Military Science and Technology
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• 제5권3호
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• pp.62-76
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• 2002

This paper describes the design of a Coordinates Tracking algorithm for EOTS and its error analysis. EOTS stabilizes the image sensors such as FLIR, CCD TV camera, LRF/LD, and so on, tracks targets automatically, and provides navigation capability for vehicles. The Coordinates Tracking algorithm calculates the azimuth and the elevation angle of EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which is generated by a Radar or an operator. In the error analysis in this paper, the unexpected behaviors of EOTS that is due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. This algorithm is verified and the error analysis is confirmed through simulations. The application of this algorithm to EOTS will improve the operational capability by reducing the time which is required to find the target and support especially the flight in a night time flight and the poor weather condition.

• Journal of the Korean Geotechnical Society
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• 제23권5호
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• pp.53-62
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• 2007

Recently, for the stabilization estimation of structures, many automatic measuring instruments with expensiveness and high accuracy have been developed and utilized. However, the existing manual measuring systems are almost impossible to measure the real-time for the whole surface of large-scale structures and an automatic measuring system has disadvantages with demanding enormous expense. In this study, 3D digital visual monitoring system was developed by using digital photogrammetry technique. To confirm application of developed system, it was applied to the measurement of the wall displacement of concrete surface and displacement measurement of reinforced-soil wall block. Then, the result of the test was compared with measuring value of total station. Based on the results of the comparison, the application of visual monitoring system was evaluated. The results show that the developed visual monitoring system could be available in displacement measure of structures.

• Korean Journal of Optics and Photonics
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• 제21권4호
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• pp.151-160
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• 2010

When the optical image stabilization is implemented by moving one of the lens groups in a zoom system, decentration should be considered in the optical design process. Although it is partially possible to calibrate optical performances in an optical system with non-symmetrical elements by using a lot of commercial software, the results of calibrating longitudinal aberrations have some calibration errors because of the lack of precise consideration of decentered optical systems. In particular, the amount of distortion in paraxial ray tracing is different from the experimental value because paraxial ray tracing in the optical system is not useful. In this paper, in order to solve this problem being from various commercial lens design software, the set of equations of paraxial ray tracing in a zoom lens system with the non-symmetrical elements like decentration or tilt are theoretically induced. Then, the methods to calibrate the equations of longitudinal aberrations by using these equations in a non-symmetrical optical system are presented. The method of calibrating longitudinal aberrations can in practice be used to correct hand shaking effects in a zoom lens system.