• IEMEK Journal of Embedded Systems and Applications
• /
• v.11 no.5
• /
• pp.277-285
• /
• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.1A
• /
• pp.1-9
• /
• 2000

This paper presents the error performance of 16 star-QAM with diversity reception in microcell systems in the presence of additive white Gaussian noise(AWGN) and cochannel interference. The differential detection of 16 star-QAM is split into phase detection and amplitude detection. This technique can reduce the degradation of error performance which is due to fading and the complexity of receiver. Diversity reception is proposed to improve the degradation of error performance due to fading. Equal gain and maximal ratio combinings were adopted for the phase detection and the amplitude detection, respectively. The performance of 16 star-QAM was evaluated for various of Rician factor K, maximum Doppler frequency f_DT, signal to cochannel interference ratio and diversity branch L.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_2
• /
• pp.737-746
• /
• 2022

Utilizing weather independent SAR images along with machine learning based object detector is effective in robust vessel monitoring. While conventional SAR images often applied amplitude data from Single Look Complex, exploitation of polarimetric parameters acquired from multiple polarimetric SAR images was yet to be implemented to vessel detection utilizing machine learning. Hence, this study used four polarimetric parameters (H, p₁, DoP, DPRVI) retrieved from eigen-decomposition and two backscattering coefficients (γ₀, _VV, γ₀, _VH) from radiometric calibration; six bands in total were respectively exploited from 52 Sentinel-1 SAR images, accompanied by vessel training data extracted from AIS information which corresponds to acquisition time span of the SAR image. Evaluating different cases of combination, the use of polarimetric indexes along with amplitude values derived enhanced vessel detection performances than that of utilizing amplitude values exclusively.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.5
• /
• pp.380-388
• /
• 2004

This study proposed an improved spike detection algorithm which automatically detects suitable spike threshold on the amplitude of surface electromyography(SEMG) signal during isometric contraction. The EMG data from the low back muscles was obtained in six channels and the proposed signal processing algorithm is compared with the median frequency and Gabriel's spike parameter. As a result, the reliability of spike parameter was inferior to the median frequency. This fact indicates that a spike parameter is inadequate for analysis of multi-channel EMG signal. Because of uncertainty of fixed spike threshold, the improved spike detection algorithm was proposed. It automatically detects suitable spike threshold depending on the amplitude of the EMG signal, and the proposed algorithm was able to detect optimal threshold based on mCFAR(modified Constant False Alarm Rate) in the every EMG channel. In conclusion, from the reliability points of view, neither median frequency nor existing spike detection algorithm was superior to the proposed method.

• Smart Structures and Systems
• /
• v.2 no.2
• /
• pp.141-154
• /
• 2006

Recently, the Hilbert-Huang transform (HHT) has gained considerable attention as a novel technique of signal processing, which shows promise for the system identification and damage detection of structures. This study investigates the effectiveness and accuracy of the HHT method for the system identification and damage detection of structures through a series of experiments. A multi-degree-of-freedom (MDOF) structural model has been constructed with modular members, and the columns of the model can be replaced or removed to simulate damages at different locations with different severities. The measured response data of the structure due to an impulse loading is first decomposed into modal responses using the empirical mode decomposition (EMD) approach with a band-pass filter technique. Then, the Hilbert transform is subsequently applied to each modal response to obtain the instantaneous amplitude and phase angle time histories. A linear least-square fit procedure is used to identify the natural frequencies and damping ratios from the instantaneous amplitude and phase angle for each modal response. When the responses at all degrees of freedom are measured, the mode shape and the physical mass, damping and stiffness matrices of the structure can be determined. Based on a comparison of the stiffness of each story unit prior to and after the damage, the damage locations and severities can be identified. Experimental results demonstrate that the HHT method yields quite accurate results for engineering applications, providing a promising tool for structural health monitoring.

• Journal of Magnetics
• /
• v.17 no.4
• /
• pp.298-301
• /
• 2012

In order to know the effect of surface irregularity in the detection of local wall thinning of pipeline using pulsed eddy current (PEC), the lift-off effects on PEC signal have been investigated. Three kinds of parameters in the PEC signal, which is "peak amplitude", "time to peak amplitude" and "time to zero crossing" are analyzed to separate the lift-off effects in the PEC signal. The distance from sensor to the bottom of sample which is the total thickness of combined insulator and sample is kept constant. The magnitude of the differential peak amplitude is increased with increasing sample thickness, the time to peak amplitude is increased with increasing the sample thickness. To determine the effect of lift-off, a number of balanced transient responses combining wall thinning locations and lift-off distances were plotted.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.2
• /
• pp.162-166
• /
• 2012

The instantaneous amplitude (IA) based on the higher order differential energy operator is proposed. And its general form for arbitrary order is also proposed. The various definitions of the IA and the instantaneous frequency (IF) estimators are considered. The IA and IF estimators based on the energy operators need less computational cost than the conventional IF and IA estimators exploiting the Hilbert transform. The IF and IA estimators are compared in terms of the frequency and amplitude tracking accuracy of the AM-FM signals. For noiseless case, the IA and IF estimators based on the Teager-Kaiser energy operator show better tracking performance than the IF and IA estimators based on the higher energy operators. However, under noisy condition, the IF and IA estimator based on the higher order energy operators with the order 3 and 4 show better tracking than the Teager-Kaiser energy based estimators. The IF and IA estimators are applied to signals in the various power anomalies to show their usefulness as the disturbance detectors.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.8
• /
• pp.1498-1502
• /
• 2007

There have been many different definitions of energy functions as the second statistics of a signal. In this paper, using the higher order differential energy function, we propose an algorithm separating the amplitude and frequency components in a discrete sinusoidal signal. The proposed amplitude and frequency estimation methods have less computational requirement than the existing methods. It also shows large computational advantage over the root mean square (RMS) calculation of a signal. The proposed methods can be used in the detection of abnormal events in signals on the power line. Computer simulations show that proposed frequency estimation method can detect the presence of voltage increase or decrease for a short period of time. Also, the proposed estimation methods have been compared with existing methods in terms of estimation error variance.

• Geophysics and Geophysical Exploration
• /
• v.4 no.4
• /
• pp.115-123
• /
• 2001

The bright spot is an indicator for natural gas on seismic stack sections, but it is also shown on layers where the acoustic impedance contrast is large. In order to distinguish sharply between gas and impedance contrast we need additional detailed data processing such as velocity analysis, AVO analysis and seismic complex analysis including measures of seismic amplitude, frequency, and phase. In this study, we performed detailed velocity analysis, complex analysis and DHI (Direct Hydrocarbon Indicator) analysis which is the result of amplitude variation according to the incident angles. The seismic complex analysis gives us the geological information which depends on geophysical properties at the interest layer. For the complex analysis, we computed several seismic attributes such as the instantaneous amplitude, the first and the second derivatives of the instantaneous amplitude, the instantaneous phase, the instantaneous frequency and weighted average instantaneous frequency. Then we applied these analysis techniques to a seismic data of Korea offshore which had been logged. From the result of this data analysis, it could be said that high possibility area for gas layer detection has amplitude anomalies in the instantaneous amplitude, the instantaneous frequency and the DHI section resulting from the AVO analysis. If there are not any other anomalies in detailed data processing, it will have low possibility for gas layer detection.

• Geophysics and Geophysical Exploration
• /
• v.10 no.4
• /
• pp.377-382
• /
• 2007

Several prospecting methods have been used to detect deep seated small tunnel in Korea. Tunnel interpretation of seismic method has been performed mainly by wave traveltime inversion method. But it often gives inacurate solution for the exact tunnel position because of the short distance between two measuring boreholes and picking errors of first arrivals. In this study, "error tomogram" was proposed to detect tunnel position and applied to theoretical and field dat using multi-source amplitude data.