• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.230-238
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• 1998

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2113-2115
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• 2006

This paper proposes a spatio-temporal correlation algorithm that takes advantage of the spatial and temporal correlations in video streams for error concealment. The spatio-temporal correlation algorithm sets the neighborhood area of the damaged part as a reference window, then finds the area that best matches the reference window in the previous frame. The best-matched area in the previous frame replaces the damaged part in the current frame. The results of ten variations of the proposed algorithm are compared with conventional error concealment methods. These methods include the ones applicable to P-frames as well as I-frames. The comparison results show that the proposed algorithm is very efficient for l-frame error concealment with a large motion between frames.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.580-583
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• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Journal of Ocean Engineering and Technology
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• v.35 no.5
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• pp.336-346
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• 2021

The prediction of wave conditions is crucial in the field of marine and ocean engineering. Hence, this study aims to predict the significant wave height through machine learning (ML), a soft computing method. The adopted metocean data, collected from 2012 to 2020, were obtained from the Korea Institute of Ocean Science and Technology. We adopted the feedforward neural network (FNN) and long-short term memory (LSTM) models to predict significant wave height. Input parameters for the input layer were selected by Pearson correlation coefficients. To obtain the optimized hyperparameter, we conducted a sensitivity study on the window size, node, layer, and activation function. Finally, the significant wave height was predicted using the FNN and LSTM models, by varying the three input parameters and three window sizes. Accordingly, FNN (W48) (i.e., FNN with window size 48) and LSTM (W48) (i.e., LSTM with window size 48) were superior outcomes. The most suitable model for predicting the significant wave height was FNN(W48) owing to its accuracy and calculation time. If the metocean data were further accumulated, the accuracy of the ML model would have improved, and it will be beneficial to predict added resistance by waves when conducting a sea trial test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.284-287
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• 2003

Previous stereo methods doesn't deal effectively with depth discontinuity due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper. a variable window approach is presented to estimate accurate, detailed and smooth disparities with three-dimensional disparity space. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the space. In addition, it devises the novel arbitrarily-shaped variable window to treat with disparity variations of various structure shapes. We show how our results improve on those of closely related techniques for accuracy, robustness. matching density and computing speed.

• New & Renewable Energy
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• v.19 no.3
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• pp.13-21
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• 2023

Smart windows are capable of varying their visible light transmittance (VLT) in response to changing environmental conditions. The VLT variability of architectural windows is highly valuable because it enables indoor lighting and energy environments to align with external changes. However, challenges such as high installation costs and assurance of glass visibility have prompted the exploration of alternative solutions, including models incorporating partially applied smart windows., Prior research focused on useful daylight illuminance (UDI) analysis for south-facing office buildings, pointing out suitable areas for smart-window implementation to enhance lighting control. In this study, we broadened this scope by determining optimal smart-window application zones under changing building orientation. Furthermore, we studied the correlation between building orientation and smart-window deployment areas.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.46-57
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• 1997

In this paper, we propose an efficient algorithm for adaptation of tracking windwo, which improves tracking performance of a correlation-based video tracker by rejecting background effect originated from a time-varying target. Th eproposed adaptation algorithm ajdusts the size of a tracking window by using the ratio of spatial gradient power in target region to that in backgorund region, which is especially adequate for a correlation-based tracker. Experimental results for synthetic and real image sequences show that the proposed method adapts a tracking window well to a time-varying target and so greatly suppresses background effect, which makes improvement of trakcing performance.

• Journal of The Korean Association of Information Education
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• v.9 no.4
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• pp.649-659
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• 2005

A window presentation style, either tiled window or single page design, determines the spatial arrangement of information in a modern computer-based instructional design. This study investigates the interaction between spatial ability and window presentation style in terms of student's achievement of cognitive knowledge through Web-based instruction. Seventy-one students from the Falk School in Pennsylvania were pre-tested to determine their level of spatial ability, then randomly divided into two treatment groups in order to study a Web-based instructional unit on flowering plants. The Web-based instructional package was organized with either tiled window presentation or single page presentation. A posttest measured participants'acquisition of the instructional content. Posttest and spatial ability test scores were analyzed using multi-variate linear regression for the full sample (n=71) and three sub-samples: (a) 4th and 5th grade students only, (b) female students only, and (c) 4th and 5th grade female students only. The goals of the data analysis included the examination of (i) the correlation between spatial ability and posttest scores; (ii) the correlation between window presentation style and posttest score; and (iii) the interaction between spatial ability (aptitude) and presentation style (treatment).The data from all four sample groups showed a significant relationship between spatial ability and achievement of cognitive knowledge at the 1% level of significance. The aptitude-treatment interaction between spatial ability and style of window presentation was not significant in the full sample, but was significant in the sub-samples either at the 10% or 5% level. In neither the full sample nor any sub-sample data did window presentation style have an impact on average posttest score. In all analyses, the higher the level of spatial ability, the higher the posttest score. The sub-samples revealed that students with low spatial ability performed better with the tiled window presentation, while those with high spatial ability did better with the single page presentation. Neither window presentation style was shown to better foster learning by children of all levels of spatial ability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.587-597
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• 2007

This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters to minimize search area, the matching is carried out based on this line. The experiment is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.153-160
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• 2009

In relation to digital elevation model(DEM) production using high resolution satellite imagery, existing studies present that DEM accuracy differently show according to land cover property. This study therefore proposes auto-selection method of window size for correlation matching according to land cover property of IKONOS Geo-level stereo image. For this, land cover classified image is obtained by IKONOS color image with four bands. In addition, correlation-coefficients are computed at regular intervals in pixels of the window-search area to shorten of matching time. As the results, DEM by the proposed method showed more accurate than DEM using the fixed window-size matching. We estimate that accuracy of the proposed DEM improved more than DEM by digital map and ERDAS in agricultural land.