• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.96-104
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• 1996

In this paper, we propose a new algorithm that obtains the surfac eorientation of the texture image using structural approaches. The proposed method showed that structural approaches can be effectively used in 3-D analysis of textures as well as description and segmentation without additional information. By examining fourier power spectrum of the texture image, we detemine the tilt of the textured surface. Then, 1-D projection information of the texture in the obtained tilt direction is used to compute the slant. Using the obtained information, we can compute the vanishing point, and rearrange the textured surface with lines converging to the vanishing point and lines perpendicular to the tilt direction. In the experimental results, we have ascertained the proposed algorithm can make a rpecise 3-D analysis of structural textures.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.177-182
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• 1997

A visual servoing method is proposed for a robot with a camera in hand. Specifically, vanishing point features are suggested by employing a viewing model of perspective projection to calculate the relative rolling, pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.116-125
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• 2014

Road conditions can provide important information for driving safety in driving assistance systems. The input images usually include unnecessary information and they need to be analyzed only in a region of interest (ROI) to reduce the amount of computation. In this paper, a vision-based road ROI determination algorithm is proposed to detect the road region using the positional information of a vanishing point and line segments. The line segments are detected using Canny's edge detection and Hough transform. The vanishing point is traced by a Kalman filter to reduce the false detection due to noises. The road ROI can be determined automatically and adaptively in every frame after initialization. The proposed method is implemented using C++ and the OpenCV library, and the road ROIs are obtained from various video images of black boxes. The results show that the proposed algorithm is robust.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.468-469
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• 2018

We design CNN(convolutional neural network) which is applicable to steering control system of autonomous vehicle. CNN has been widely used in many fields, especially in image classifications. But CNN has not been applied much to the regression problem such as function approximation. This is because the input of CNN has a multidimensional data structure such as image data, which makes it is not applicable to general control systems. Recently, autonomous vehicles have been actively studied, and many techniques are required to implement autonomous vehicles. For this purpose, many researches have been studied to detect the lane by using the image through the black box mounted on the vehicle, and to get the vanishing point according to the detected lane for control the autonomous vehicle. However, in detecting the vanishing point, it is difficult to detect the vanishing point with stability due to various factors such as the external environment of the image, disappearance of the instant lane and detection of the opposite lane. In this study, we apply CNN for steering control of an autonomous vehicle using a black box image of a car.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.81-81
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• 2000

We use camera to apply human vision system in measurement. To do that, we need to know about camera parameters. The camera parameters are consisted of internal parameters and external parameters. we can fix scale factor&focal length in internal parameters, we can acquire external parameters. And we want to use these parameters in automatically driven vehicle by using camera. When we observe an camera parameters in respect with that the external parameters are important parameters. We can acquire external parameter as fixing focal length&scale factor. To get lane coordinate in image, we propose a lane detection filter. After searching lanes, we can seek vanishing point. And then y-axis seek y-sxis rotation component(${\beta}$). By using these parameter, we can find x-axis translation component(Xo). Before we make stepping motor rotate to be y-axis rotation component(${\beta}$), '0', we estimate image coordinates of lane at (t+1). Using this point, we apply this system to Kalman filter. And then we calculate to new parameters whick make minimum error.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.73-82
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• 2021

According to the government's announcement of the safety management enhancement policy for small and medium-sized private construction sites, the subject of mandatory CCTV installation has been expanded from large construction sites to small and medium-sized construction sites. However, since the existing CCTV at construction sites has been used for simple control for safety management, so research is needed for monitoring of construction sites. Therefore, in this study, three vanishing points were calculated based on a single image taken with a monocular camera, and then a camera matrix containing interior orientation parameters information was determined. And the accuracy was verified by calculating the height of the target object from the height of the reference object. Through height determination experiments using vanishing points based on a monocular camera, it was possible to determine the height of target objects only with a single image without separately surveying of ground control points. As a result of the accuracy evaluation, the root mean square error was ±0.161m. Therefore, it is determined that the progress of construction work at the construction sites can be monitored through the single image taken using the single camera.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.515-520
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• 2003

This paper proposes a calibration method from two images. Camera calibration is necessarily required to obtain 3D Information from 2D images. Previous works to accomplish the camera calibration needed the calibration object or required more than three images to calculate the Kruppa equation, however, we use the geometric constraints of parallelism and orthogonality can be easily presented in man-made scenes. The task of it is to obtain intrinsic and extrinsic camera parameters. The intrinsic parameters are evaluated from vanishing points and then the extrinsic parameters which are consisted of rotation matrix and translation vector of the camera are estimated from corresponding points of two views. From the calibrated parameters, we can recover the projection matrices for each view point. These projection matrices are used to recover 3D information of the scene and can be used to visualize new viewpoints.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.73-83
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• 2019

In this paper, we propose the augmented reality(AR) based driving navigation based on robust lane detection method to dynamic environment changes. The proposed technique uses the detected lane position as a marker which is a key element for enhancing driving information. We propose Symmetrical Local Threshold(SLT) algorithm which is able to robustly detect lane to dynamic illumination environment change such as shadows. In addition, by using Morphology operation and Connected Component Analysis(CCA) algorithm, it is possible to minimize noises in the image, and Region Of Interest(ROI) is defined through region division using a straight line passing through several vanishing points We also propose the augmented reality aided visualization method for Interchange(IC) and driving navigation using reference point detection based on the detected lane coordinates inside and outside the ROI. Validation experiments were carried out to assess the accuracy and robustness of the proposed system in vairous environment changes. The average accuracy of the proposed system in daytime, nighttime, rainy day, and cloudy day is 79.3% on 4600 images. The results of the proposed system for AR based IC and driving navigation were also presented. We are hopeful that the proposed research will open a new discussion on AR based driving navigation platforms, and thus, that such efforts will enrich the autonomous vehicle services in the near future.

• Journal of the Korean Mathematical Society
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• v.35 no.1
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• pp.85-114
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• 1998

We prove the existence of solutions of the Reimann problem for a system of conservation laws of mixed type using the method of vanishing viscosity term.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.67-76
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• 2012

This paper proposes an efficient method that helps a visually impaired person to detect a pavement borderline. A pedestrian is equipped with a camera so that the front view of a natural scene is captured. Our approach analyzes the captured image and detects the borderline of a pavement in a very robust manner. Our approach performs the task in two steps. In a first step, our approach detects a vanishing point and vanishing lines by applying an edge operator. The edge operator is designed to take a threshold value adaptively so that it can handle a dynamic environment robustly. The second step is to determine the borderlines of a pavement based on vanishing lines detected in the first step. It analyzes the vanishing lines to form VRays that confines the pavement only. The VRays segments out the pavement region in a radial manner. We compared our approach against Canny edge detector. Experimental results show that our approach detects borderlines of a pavement very accurately in various situations.