• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2962-2964
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• 1999

We know the traffic information about the velocity and position of vehicle by extraction and tracking vehicle from continuosly obtained road image of camera. The conventional method of vehicle detection indicate increment of error due to headlight and taillight in night road image. This paper show such as vehicle detection of binary, Edge detection. amalgamation of image are applied to extract the vehicle, and Kalman filter is adaptive methods for tracking position and velocity of vehicle.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.871-879
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• 1997

The comversion of printed maps into computerixed data bases is an enormous rask. Thus the autmaotion of the conversion process is essential. Efficient computer representation of printed maps and line drawings depends on codes assigened to chracaters, symbools, and vestor representation of the graphics. In many cases, maps ard constructed in a number of layers, where each layer is printed in a distinct color, and it represents a subste of the map infromation. In order to properly repressnet road information from color map images, an automatic road extraction algorithm is proposed. Road image is separated from graghics by color segmentation, and then restored by the proposed concurrent conditional dilation operation. The internal and external noise of the road image is eliminated by opening and closing operation. By thining and vectorizing line segments, the desited road information is extracted.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.3
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• pp.61-70
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• 2001

This paper presents a new method to extract semi-automatically roads from high spatial resolution satellite imagery. This method is based both on wavelet transform and on multiresolution analysis combined in the "$\grave{a}$ trous" algorithm. As an urban road network consists on different classes of streets, multiresolution processing allows to extract the streets class by class. The method was applied to a KVR-1000 image on a part of Busan Metropolitan City. The method was carried out for the road extraction of three different widths and it succeeded in extracting good fitted strips. The accuracy analysis for three types of streets was also performed. The overall accuracy in 4 pixels of width is 80.5%. The result suggests that this method can be used to update road networks in the studied urban network. In summary, the multiresolution approach based on the wavelet transform, used in this study, is regarded as one of effective methods to extract urban road network from high spatial resolution satellite images.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.61-68
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• 2004

In this paper, we suggest an automatic technique to obtain 3-D road information in complex urban areas using road pavement markings. This method is composed of following three main steps. The first step is extracting the pavement markings from aerial images, the second one is matching the same pavement markings in two aerial images, and the last one is obtaining the 3-D coordinates of those using EOP(exterior orientation parameters) of aerial images. Here, we focus on the first and second step because the last step can be performed by using the well hewn collinearity condition equation. We used geometric properties and spatial relationships of the pavement markings to extract the lane line markings on the images and extracted arrow lane markings additionally using template matching. And then, we obtained 3-D coordinates of the road using relational matching for the pavement markings. In order to evaluate the accuracy of extraction, we did a visual inspection and compared the result of this technique with those measured by digital photogrammetric system.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.359-364
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• 2014

In this paper, we propose a method for extracting a road area by using the mean-shift method and connected-component method. Mean-shift method is very effective to divide the color image by the method of non-parametric statistics to find the center mode. Generally, the feature points of road are extracted by using the information located in the middle and bottom of the road image. And it is possible to extract a road region by using this feature-point and the partitioned color image. However, if a road region is extracted with only the color information and the position information of a road image, it is possible to detect not only noise but also off-road regions. This paper proposes the method to determine the road region by eliminating the noise with the closing / opening operation of the morphology, and by extracting only the portion of the largest area using a connected-components method. The proposed method is simulated and verified by applying the captured road images.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.228-230
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• 2009

Lane extraction is basically required for a driving car to understand its external road environments via a camera. In this paper, a lane extraction method using "Sobel Intensity Profile" is described. The Sobel intensity profile is obtained using only vertical edge components of Sobel edge outputs, and used to yield fitted lines for lanes. The RANAC algorithm is applied to fit lines using only inliers. Experimental results have shown the reliability of the proposed lane extraction method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.527-533
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• 2004

This study has based on RTKGPS and DGPS and Digital Video Camera to 3-dimensional position data of road, as a Road Spatial Information. Economic efficiency analysis was applied to road spatial information system built up by four different methods such as conventional surveying, RTK GPS, DGPS, and Digital Video Camera. As a result of analysis, it was shown conventional surveying 100%, it was shown that about 64% in RTKGPS, it was shown that about 63% in DGPS, it was shown that about 37% in Digital Video Camera cost-saving.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.171-181
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• 2005

The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lane­related information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.

• Smart Structures and Systems
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• v.31 no.2
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• pp.155-169
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• 2023

The quasi-static component of the moving vehicle-induced dynamic response is promising in damage detection as it is sensitive to bridge damage but insensitive to environmental changes. However, accurate extraction of quasi-static component from the dynamic response is challenging especially when the vehicle velocity is high. This paper proposes an adaptive quasi-static component extraction method based on the modified variational mode decomposition (VMD) algorithm. Firstly the analytical solutions of the frequency components caused by road surface roughness, high-frequency dynamic components controlled by bridge natural frequency and quasi-static components in the vehicle-induced bridge response are derived. Then a modified VMD algorithm based on particle swarm algorithm (PSO) and mutual information entropy (MIE) criterion is proposed to adaptively extract the quasi-static components from the vehicle-induced bridge dynamic response. Numerical simulations and real bridge tests are conducted to demonstrate the feasibility of the proposed extraction method. The results indicate that the improved VMD algorithm could extract the quasi-static component of the vehicle-induced bridge dynamic response with high accuracy in the presence of the road surface roughness and measurement noise.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.123-128
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• 2003

Data acquired from digital Imagery were processed via Delphi, an object-oriented programming language to develop a computer aided program, that allows us to build up the information on road horizontal alignment(BC, EC, R, IP). And the developed program could maximize the visual effects better than traditional programs, because it used many image data. Comparing with data from traditional horizontal alignment extraction programs based on the principle of least square method, the data acquired by horizontal alignment information and kinematic GPS out of the developed road information systems showed the enhanced accuracy of IP value up to about 2m in the direction of X, Y axes, where the accuracy of curve radius(R) becomes enhanced up to about 2.5 m.