• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.468-475
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• 2018

In medical ultrasound imaging, frequency-dependent attenuation downshifts and reduces a center frequency and a frequency bandwidth of received echo signals, respectively. This causes considerable errors in quadrature demodulation (QDM), result in lowering signal-to-noise ratio (SNR) and contrast resolution (CR). To address this problem, adaptive dynamic QDM (ADQDM) that estimates center frequencies along depth was introduced. However, the ADQDM often fails when imaging regions contain hypoechoic regions. In this paper, we introduce a valid region-based ADQDM (VR-ADQDM) method to reject the misestimated center frequencies to further improve SNR and CR. The valid regions are regions where the center frequency decreases monotonically along depth. In addition, as a low-pass filter of QDM, Gaussian wavelet based dynamic filtering was adopted. From the phantom experiments, average SNR improvements of the ADQDM and the VR-ADQDM over the traditional QDM were 1.22 and 5.27 dB, respectively, and the corresponding maximum SNR improvements were 2.56 and 10.58 dB. The contrast resolution of the VR-ADQDM was also improved by 0.68 compared to that of the ADQDM. Similar results were obtained from in vivo experiments. These results indicate that the proposed method would offer promises for imaging technically-difficult patients due to its capability in improving SNR and CR.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.289-294
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• 2002

A valid speech-sound block can be classified to provide important information for speech recognition. The classification of the speech-sound block comes from the MRA(multi-resolution analysis) property of the DWT(discrete wavelet transform), which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract valid speech-sounds in terms of position and frequency range. It needs some numerical methods for an adaptive DWT implementation and performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising SNR(signal-to-nolle ratio).

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.360-370
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• 2004

Adaptive mesh refinement(AMR) is one of the popular computational simulation techniques used in various scientific and engineering fields. Although AMR data is organized in a hierarchical multi-resolution data structure, traditional volume visualization algorithms such as ray-casting and splatting cannot handle the form without converting it to a sophisticated data structure. In this paper, we present a hierarchical multi-resolution splatting technique using k-d trees and octrees for AMR data that is suitable for implementation on the latest consumer PC graphics hardware. We describe a graphical user interface to set transfer function and viewing / rendering parameters interactively. Experimental results obtained on a general purpose PC equipped with an nVIDIA GeForce3 card are presented to demonstrate that the proposed techniques can interactively render AMR data(over 20 frames per second). Our scheme can easily be applied to parallel rendering of time-varying AMR data.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.610-615
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• 2015

The accuracy and precision of video-based remote gaze trackers is affected by numerous factors (e.g. the head movement of the participant). However, it is challenging to control all factors that have an influence, and doing so (e.g., using a chin-rest to control geometry) could lead to losing the benefit of using gaze trackers, i.e., the ecological validity of their unobtrusive nature. We propose an adaptive zoom-based gaze tracking technique, ZoomTrack that addresses this problem by improving the resolution of the gaze tracking results. Our approach magnifies a region-of-interest (ROI) and retrieves gaze points at a higher resolution under two different zooming modes: only when the gaze reaches the ROI (temporary) or whenever a participant stares at the stimuli (omnipresent). We compared these against the base case without magnification in a user study. The results are then used to summarize the advantages and limitations of our technique.

• Journal of the Korean Society for Railway
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• v.20 no.3
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• pp.374-381
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• 2017

Concrete sleepers, installed on majority of railroad track in this nation can, if not maintained properly, threaten the safety of running trains. In this paper, an algorithm for automatically identifying cracks in a sleeper image, taken by high-resolution camera, is developed based on Adaboost, known as the strongest adaptive algorithm and most actively utilized algorithm of current days. The developed algorithm is trained using crack characteristics drawn from the analysis results of crack and non-crack images of field-installed sleepers. The applicability of the developed algorithm is verified using 48 images utilized in the training process and 11 images not used in the process. The verification results show that cracks in all the sleeper images can be successfully identified with an identification rate greater than 90%, and that the developed automatic crack identification algorithm therefore has sufficient applicability.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.1-8
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• 2002

The color interpolation scheme can play an important role in overcoming the physical limitation of the CCD image sensor and in increasing the resolution of color signals, while most conventional approaches result in blurred edges and false color artifacts. In this paper, we have proposed an improved edge-adaptive color interpolation scheme for a progressive scan CCD image sensor with RGB color filter array The edge indicator function proposed utilizes not only the within-channel correlation but also the cross-channel correlation, and reflects the edge characteristics of an image adaptively. The color components unavailable for at each channel are interpolated along the edge direction, not across the edges, so that aliasing artifacts are supressed. Furthermore, we eliminated false color artifacts resulting from the color image formation model in the edge-adaptive color interpolation scheme by adopting the switching algorithm based on the color edge detection. Simulation results of the proposed algorithm indicate that the improved edge-adaptive color interpolation scheme produces quantitatively better and visually more pleasing results than conventional approaches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.97-102
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• 2010

A laser speckle is a random pattern that has a granular appearance produced by reflected light when a coherent laser illuminates an irregular course surface. Most important property of laser speckle is detecting micro-vascular. Speckle image needs image processing to detect micro-vascular. This paper proposes a new image processing method for laser speckle, adaptive window method that adaptively processes laser speckle images in the spatial. Conventional fixed window based LASCA has shortcoming in that it uses the same window size regardless of target areas. Inherently laser speckle contains undesired noise. Thus a large window is helpful for removing the noise but it results in low resolution of image. Otherwise a small window may detect micro vascular but it has limits in noise removal. To overcome this trade-off, we newly introduce the concept of adaptive window method to conventional laser speckle image analysis. We have compared conventional LASCA and its variants with the proposed method in terms of image quality and processing complexity.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1166-1178
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• 2016

In Internet of Things (IoT) environments, billions of interconnected devices and multimedia sensors generate a huge amount of multimedia traffic. Since the environment are in general deployed as a server-centric architecture wireless sensor networks could be bottlenecks between IoT gateways and IoT devices. The bottleneck causes high power consumption of the device and triggers very heavy network overload by transmission of sensing data. The deterioration could decrease the quality of multimedia streaming service due to delay, loss, and waste of device power. Thus, in this paper, we propose a context-based adaptive multimedia streaming scheme to support enhanced QoS and low power consumption in IoT environments. The goal of the scheme is to increase quality score per voltage of the streaming service, given an adaptation algorithm with context that are classified network and hardware such as throughput, RTT, and CPU usage. From the both context, the quality score per voltage is used in the comparison of a only network context-based adaptive multimedia streaming scheme, a fixed multimedia streaming and our scheme. As a result, we achieves a high improvement that means the quality score per voltage is increased up to about 4, especially in case of resolution change.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1413-1422
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• 2012

Adaptive back stepping control technique may provide robust control characteristics under parameter perturbation caused by changing external condition. In order to synthesize a high-precision velocity controller for IPMSM(Interior Permanent Magnet Synchronous Motor) using this method, the period of control loop should be very small. However, because of the resolution of the encoder for speed measurement, control cycle is limited, which makes it difficult to improve the performance of the controller. This paper proposes a velocity controller design method based on nonlinear adaptive back-stepping method to accomplish fast and accurate performance. Here, an EKF(Extended Kalman Filter) method is incorporated for the estimation of the motor speed into the design of a speed controller using adapted back-stepping control technique. The performance of the proposed controller is demonstrated through simulation using PSIM.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.97-100
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• 2009

The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 and 2000 using a dynamic technique, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series for tracking changes on the ground surface. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.