• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.164-164
• /
• 2000

This paper proposes a moving window technique that extracts lanes and vehicles using the images captured by a CCD camera equipped inside an automobile in real time. For the purpose, first of all the optimal size of moving window is determined based upon speed of the vehicle, road curvature, and camera parameters. Within the moving windows that are dynamically changing, lanes and vehicles are extracted, and the vehicles within the driving lanes are classified as obstacles. Assuming highway driving, there are two sorts of image-objects within the driving lanes: one is ground mark to show the limit speed or some information for driving, and the other is the vehicle as an obstacle. Using characteristics of three-dimension objects, a neural network can be trained to distinguish the vehicle from ground mark. When it is recognized as an obstacle, the distance from the camera to the front vehicle can be calculated with the aids of database that keeps the models of automobiles on the highway. The correctness of this measurement is verified through the experiments comparing with the radar and laser sensor data.

• Structural Engineering and Mechanics
• /
• v.62 no.5
• /
• pp.631-642
• /
• 2017

Accurate actuator tracking plays an important role in real-time hybrid simulation (RTHS) to ensure accurate and reliable experimental results. Frequency-domain evaluation index (FEI) interprets actuator tracking into amplitude and phase errors thus providing a promising tool for quantitative assessment of real-time hybrid simulation results. Previous applications of FEI successfully evaluated actuator tracking over the entire duration of the tests. In this study, FEI with moving window technique is explored to provide post-experiment localized actuator tracking assessment. Both moving window with and without overlap are investigated through computational simulations. The challenge is discussed for Fourier Transform to satisfy both time domain and frequency resolution for selected length of moving window. The required data window length for accuracy is shown to depend on the natural frequency and structural nonlinearity as well as the ground motion input for both moving windows with and without overlap. Moving window without overlap shows better computational efficiency and has potential for future online evaluation. Moving window with overlap however requires much more computational efforts and is more suitable for post-experiment evaluation. Existing RTHS data from Network Earthquake Engineering Simulation (NEES) is utilized to further demonstrate the effectiveness of the proposed approaches. It is demonstrated that with proper window size, FEI with moving window techniques enable accurate localized evaluation of actuator tracking for real-time hybrid simulation.

• Phonetics and Speech Sciences
• /
• v.2 no.3
• /
• pp.165-170
• /
• 2010

In this study, the most stable portion was identified using 5% moving window during /a/ sustained phonation in normal and pathologic voice signals and the perturbation values were compared between normal and pathologic voices at the mid-point and at the most stable portion using moving window, respectively. The results revealed that some severe pathologic voice signals can be eligible for perturbation analysis by identifying the most stable portion with Err less than 10. In addition, the perturbation acoustic parameters did not differentiate the pathologic voice signals from the normal voice signals when the mid-point was selected to measure the perturbation analysis(p>0.05). However, significantly higher %shimmer and lower SNR values were observed in pathologic voices (p<0.05) when the most stable portion was selected by moving window. In conclusion, moving window could identify the most stable portion objectively which can allow toget the minimum perturbation values (%jitter, %shimmer) and maximum SNR values. Thus, moving window technique can be applicable for more reliable and accurate perturbation acoustic analysis.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.7
• /
• pp.673-679
• /
• 2012

This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.3
• /
• pp.57-69
• /
• 2000

A moving window technique for detecting a lane and obstacles using the Images captured by a CCD camera attached in an automobile, is proposed in this paper To process the dynamic images in real time, there could be many constraints on the hardware To overcome these hardware constraints and to detect the lane and obstacles in real time, the optimal size of window IS determined based upon road conditions and automobile states. By utilizing the sub-Images inside the windows, detection of the lane and obstacles become possible m real time. For each Image frame, the moving windows are re-determined following the predicted directions based on Kalman filtering theory to Improve detection accuracy, as well as efficiency The feasibility of proposed algorithm IS demonstrated through the simulated experiments of highway driving.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.7
• /
• pp.2332-2338
• /
• 2011

In this study, we proposed a new promising idea of utilizing moving window principal component analysis (MWPCA) as a sensitive diagnostic tool to detect the presence of peak position shift. In this approach, the moving window is constructed from a small data segment along the wavenumber axis. For each window bound by a narrow wavenumber region, separate PCA analysis was applied. Simulated spectra with complex spectral feature variations were analyzed to explore the possibility of MWPCA technique. This MWPCA-based detection of the peak shift, potentially coupled with 2D correlation analysis to provide additional verification, may offer an attractive solution.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.889-893
• /
• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.14 no.4
• /
• pp.684-693
• /
• 2011

Measurement time delay in the transfer alignment is very important. It has been well known that the time delay degrades the alignment performance and makes some navigation errors on the transfer alignment of slave INS(SINS). Therefore there are many schemes to eliminate that time delay but the compensation technique through the estimation by Kalman filter through modeling the time delay as a random constant is generally used. In the case of change over measurement time delay or the large measurement time delay, estimation performance in the existing compensation technique is degraded because model of time delay is not correct any more. In this paper, we propose the method to keep the time delay almost constant even though in the abnormal communication state and very small through feedback compensation using double buffer. Double buffer consists of two moving window to temporarily store measurements from master INS and slave INS in real time.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.7
• /
• pp.569-581
• /
• 1989

This paper deals with a tracking algorithm based on integral projection which tracks moving targets with varying brightness and size. An adaptive windowing technique is employed to reduce the sensitivity of the system to the complex background image and also to reduce the computational load. The threshold value is determined by considering both the size and the threshold value of the brightness intensity of the recognized target obtained in the previous processing step. Window position is estimated by using the information of the velocity and acceleration of the target. And integral projection is applied to find the position of the target in the window accurately. Experimental results show that moving targets with varying brightness and size can be tracked properly in noisy environments.

• Journal of information and communication convergence engineering
• /
• v.9 no.6
• /
• pp.747-752
• /
• 2011

The position detection of overlapping area in the interframe for image stitching using auto and cross correlation function (ACCF) and compounding one image with the stitching algorithm is presented in this paper. ACCF is used by autocorrelation to the featured area to extract the filter mask in the reference (previous) image and the comparing (current) image is used by crosscorrelation. The stitching is detected by the position of high correlation, and aligns and stitches the image in shifting the current image based on the moving vector. The ACCF technique results in a few computations and simplicity because the filter mask is given by the featuring block, and the position is enabled to detect a bit movement. Input image captured from CMOS is used to be compared with the performance between the ACCF and the window correlation. The results of ACCF show that there is no seam and distortion at the joint parts in the stitched image, and the detection performance of the moving vector is improved to 12% in comparison with the window correlation method.