• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.123-132
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• 1998

This paper presents a road detection technique for spaceborne synthetic aperture radar (SAR) images. Roads are important cartographic features. We incorporate an active contour model called snake as a model for the road and define a new external energy for snake which is appropriate for the road. Detecting roads in spaceborne SAR images is very difficult without other information. In this paper, digital maps are utilized to obtain the initial position and shape for snake. Only approximate geodetic location of roads appearing in SAR images can be known through geocoding process and usual digital maps also have location errors. Therefore, there exist large location offsets between the two data. By introducing initial matching procedure, the errors are reduced significantly. Then we initialize the snake's shape using the roads extracted from digital map and minimize the energies of all snake points to detect roads. We outline two problems in detection and propose a method that mitigates them.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.81-89
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• 2009

Dancer systems are typical equipment for attenuation of tension disturbances. Lately, demands for high speed roll-to-roll machines are rising but it is prior to attenuate the tension variation on the web entering into the printing zone to achieve the speed increment. Maintaining a constant tension before the first printing cylinder is the key of high speed, high quality printing. Dancer has been researched in two ways, whether it is controlled or not. The first one is active dancer and the other one is passive dancer. In the active dancer, a position of idle roll of dancer is measured and the roll is moved by external hydraulic cylinder to control tension disturbances. While the passive one composed with spring, damper and idle roll has no external actuator to position the idle roll. The tension disturbance causes movement of dancer roll and the displacement of the roll regulates the tension variation. On the other hand a composite type of dancer is applied for roll-to-roll printing machines. It has same apparatus as passive dancer. The displacement of roll is measured and front(or rear) driven roller is controlled to position the roll. In this paper, it is presented an analysis of pendulum dancer including position feedback PI control and logic for PI gain tuning in roll-to-roll machines. Pole-zero map and root locus with varying system parameters gives a design method for control of the dancer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.586-594
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• 2012

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on AP's probabilistic position estimation, we develop an AP distribution map and new pattern matching algorithm for position estimation. The developed approaches can strengthen the advantages of Radio fingerprint based Wi-Fi Positioning System, especiall on the algorithms and data handling. Compared on the existing approaches of fingerprint pattern matching algorithm, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore all fingerprint data have been harvested from the actual measurement of radio fingerprint of Seoul, Kangnam area. This can approve the practical usefulness of proposed methodology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.741-749
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• 2022

Major space agencies are planning for the rover-based lunar exploration since water-ice was detected in permanently shadowed regions (PSR). Although sunlight does not directly reach the PSRs, it is expected that reflected sunlight sustains a certain level of low-light environment. In this research, the indoor testbed was made to simulate the PSR's lighting and topological conditions, to which low light enhancement methods (CLAHE, Dehaze, RetinexNet, GLADNet) were applied to restore image brightness and color as well as to investigate their influences on the performance of feature extraction and matching methods (SIFT, SURF, ORB, AKAZE). The experiment results show that GLADNet and Dehaze images in order significantly improve image brightness and color. However, the performance of the feature extraction and matching methods were improved by Dehaze and GLADNet images in order, especially for ORB and AKAZE. Thus, in the lunar exploration, Dehaze is appropriate for building 3D topographic map whereas GLADNet is adequate for geological investigation.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.2
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• pp.17-24
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• 2014

This paper proposes an automatic extraction method of control point based on Geospatial Web Service. The proposed method consists of 3 steps. 1) The first step is to acquires reference data using the Geospatial Web Service. 2) The second step is to finds candidate control points in reference data and the target image by SURF algorithm. 3) By using RANSAC algorithm, the final step is to filters the correct matching points of candidate control points as final control points. By using the Geospatial Web Service, the proposed method increases operation convenience, and has the more extensible because of following the OGC Standard. The proposed method has been tested for SPOT-1, SPOT-5, IKONOS satellite images and has been used military standard data as reference data. The proposed method yielded a uniform accuracy under RMSE 5 pixel. The experimental results proved the capabilities of continuous improvement in accuracy depending on the resolution of target image, and showed the full potential of the proposed method for military purpose.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.81-90
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• 2004

Because satellite images include geometry distortions according to photographing conditions and sensor property, and their spatial and radiational resolution and spectrum resolution are different, it is so difficult to make a precise results of analysis. For comparing more than two images, the precise geometric corrections should be preceded because it necessary to eliminate systematic errors due to basic sensor information difference and non-systematic errors due to topographical undulations. In this study, we did sensor modeling using satellite sensor information to make a basic map of change detection for artificial topography. We eliminated the systematic errors which can be occurred in photographing conditions using GCP and DEM data. The Kompsat EOC images relief could be reduced by precise rectification method. Classifying images which was used for change detections by city and forest zone, the accuracy of the matching results are increased by 10% and the positioning accuracies also increased. The result of change detection using basic map could be used for basic data fur GIS application and topographical renovation.

• The Korean Journal of Ecology
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• v.18 no.3
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• pp.307-321
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• 1995

Division of ecoregions having respective functions was attempted through quantitative and qualitative analysis on vegetation diversity, and heterogeneity and on soil environment of the study sites. Field research was carried out in a square of 81 ㎢ around Andongpo (126°38'E, 37°30'N), Kimpo-gun, Kyonggi provice. Conventional methods applied are as follows: classical syntaxonomy by the Zurich-Montpellier School, interpolation method to determine the degree of diversity, heterogeneity and distribution pattern of vegetation, and correlation analysis between soil properties and plant communities. 41 plant communities were identified and composed of 6 forests, 4 mantle and 31 herb communities including 6 saltmarsh plant communities. In a mesh, number of plant communities was highly correlated to the number of species. The highest number of plant community and species was 25 communities·km-2·mesh-1 and 381 species· km-2·mesh-1 ,and the highest value of vegetation heterogeneity was 28.1 species· community-1·mesh-1. Their lowest numbers were 4 communities·km-2·mesh-1. and 28 species·km-2·mesh-1. and 7 species·community-1·mesh-1, respectively. Contour map on vegetation diversity and heterogeneity enabled us to establish two regions; coastal and inland vegetation. Isoline 〔150〕,〔10〕and〔10〕and〔15〕on the species diversity, the community diversity and the vegetation heterogeneity, respectively, were regarded as ecolines in the study area. Cl- content was recognized as the most important factor from correlation analysis between soil properties. Ordination of sites indicated that the study area be divided into two edaphic types: inland and coastal habitats. It was considered that the extent of desalinization in soil played a major role in determining the species composition in the reclamed area. By matching edaphic division of habitats with division of vegetation structures, designation of ecoregion was endorsed. The approach of current study was suggested as an effective tool to implement an assessment of the vegetation dynamics by the disparity of natural environment and anthropogenic interferences.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.700-710
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• 2009

A computer vision technique of estimating the location of an unmanned ground vehicle is proposed. Identifying the location of the unmaned vehicle is very important task for automatic navigation of the vehicle. Conventional positioning sensors may fail to work properly in some real situations due to internal and external interferences. Given a DSM(Digital Surface Map), location of the vehicle can be estimated by the registration of the DSM and multiview range images obtained at the vehicle. Registration of the DSM and range images yields the 3D transformation from the coordinates of the range sensor to the reference coordinates of the DSM. To estimate the vehicle position, we first register a range image to the DSM coarsely and then refine the result. For coarse registration, we employ a fast random sample matching method. After the initial position is estimated and refined, all subsequent range images are registered by applying a pair-wise registration technique between range images. To reduce the accumulation error of pair-wise registration, we periodically refine the registration between range images and the DSM. Virtual environment is established to perform several experiments using a virtual vehicle. Range images are created based on the DSM by modeling a real 3D sensor. The vehicle moves along three different path while acquiring range images. Experimental results show that registration error is about under 1.3m in average.