• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.723-728
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• 2010

This study proposed a design of a portable device for measuring heart rate using photoplethysmograph signal to minimize load of a nurse increased from insufficiency of an internal hospital nurse, and algorithm to measure reliable heart rate in PPG signals despite the existence of patient's motion artifacts. The proposed method for measuring heart rate is the method to minimize the motion interference by using the adaptive filter based on harmonic characteristic of PPG signal. To evaluate the performances of the a portable device implemented by the proposed method, we used several motion artifacts including finger and wrist movements; we then compared out results with the performance of the moving average filter. In this results, the proposed method showed a better performance than that of the moving average filter. Therefore, when nurses use the a portable device for measuring heart rate proposed in this study, it will enable to improve nurse work and to measure the reliable heart rate.

• The Journal of the Acoustical Society of Korea
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• v.11 no.3
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• pp.53-60
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• 1992

Many adaptive beamforming methods have been studied for interference cancellation and speech signal enhancement in telephone conference and auditorium. Main aspect of adaptive beamforming methods for speech signal processing is different from radar, sonar and seismic signal processing because desire output signal should be apt to the human ear. Considering that phase of speech is quite insensible to the human ear, Sondhi proposed a nonlinear constrained optimization technique whose constraint was on the magnitude transfer function from the source to the output. In real environment the phase response of the speech signal affects the human auditorium system. So it is desirable to design linear phase system. In this paper, linear phase beamformer is proposed and sample processing algorithm is also proposed for real time consideration Simulation results show that the proposed algorithm yields more consistent beam patterns and deep nulls to the noise direction than Sondhi's.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1820-1826
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• 2001

In this paper, we present a modeling scheme for the already-installed two-wire home phone lines with arbitrary topologies and show that the inter-symbol interference due to the topology can be removed using an adaptive equalizer. The transmission characteristics of the arbitrary-configured two-wire home phone lines can be analyzed through the ABCD matrices. The simulation result shows that the impedance mismatch due to the branch lines renders nulls in the frequency response or delayed pulses in the impulse response. These nulls or delayed pulses cause inter-symbol interference that inhibits correct signal detection. An adaptive equalizer is shown to be effective in eliminating the interference. Also, the simulation result shows that the equalizer converges in 1.5 ms at a data rate of 1 Msps at signal-to-noise ratios greater than 15 dB. In addition, from the result of relation between E$\_$b//N$\_$and BER(Bit Error Rate), we can see that E$\_$b//N$\_$o/ more than 19 dB is required for the data communication with a BER less than 10$\^$-5/.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.23-31
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• 2009

Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.116-125
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• 2014

Road conditions can provide important information for driving safety in driving assistance systems. The input images usually include unnecessary information and they need to be analyzed only in a region of interest (ROI) to reduce the amount of computation. In this paper, a vision-based road ROI determination algorithm is proposed to detect the road region using the positional information of a vanishing point and line segments. The line segments are detected using Canny's edge detection and Hough transform. The vanishing point is traced by a Kalman filter to reduce the false detection due to noises. The road ROI can be determined automatically and adaptively in every frame after initialization. The proposed method is implemented using C++ and the OpenCV library, and the road ROIs are obtained from various video images of black boxes. The results show that the proposed algorithm is robust.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.277-282
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• 2012

In this paper, we present a real-time eye contact system for realistic telepresence using a Kinect depth camera. In order to generate the eye contact image, we capture a pair of color and depth video. Then, the foreground single user is separated from the background. Since the raw depth data includes several types of noises, we perform a joint bilateral filtering method. We apply the discontinuity-adaptive depth filter to the filtered depth map to reduce the disocclusion area. From the color image and the preprocessed depth map, we construct a user mesh model at the virtual viewpoint. The entire system is implemented through GPU-based parallel programming for real-time processing. Experimental results have shown that the proposed eye contact system is efficient in realizing eye contact, providing the realistic telepresence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.763-770
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• 2002

Recognition of CW Morse signals can be divided into several phases such as detection of tones and spaces, signal processing for removing noise from detected signals, decision of tones/spaces, mapping a sequence of tones and spaces into characters, error correction of a character message with textual repetition. In this paper, in order to cope with signal fading effectively we propose a signal detection method of identifying peaks in the frequency domain and present techniques for combining multiple frequency peaks and for removing residual signal components and noise. LMS adaptive method is applied for decision of tones/spaces, and initial value setting and malfunctioning conditions are analyzed. In recognition experiments, we used CW Morse signals collected by radio receivers and found that the proposed method achieves good recognition performance even in severe fading conditions.