• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.177-185
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• 1998

There is an increasing request for 3D data and outlines on building for urban planning and design. This paper describes an approach to extract building using Digital Surface Models(DSM) and stereo pairs of aerial images. DSM contain informations not only about the topographic surface like Digital Elevation Models(DEM), but also about buildings and other objects higher than the surrounding topographic surface, e.g. tees. We therefore describe our approach consisting of two step procedures. The first step of the approach is to generate DSM by stereo matching using Maximum Likelihood Estimation and Dynamic Programming. The proposed stereo matching is using the cost function for finding the disparity between the left and right image, and the Dynamic Programming for solving the stereo matching problem. The second step is to detect building outlines using the DSM and the edge informations extracted from a digital aerial image by Sobel Operator. The overlay analysis of the DSM and the edge information by Sobel Operator was efficient to detect building outlines.

• Journal of the Korean Vacuum Society
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• v.2 no.2
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• pp.161-165
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• 1993

The geometrical and electronic structure of epitaxially grown Ge on Si(100) and Si(111) surfaces has been studied by scanning tunneling microscopy. Since Ge atoms could be distinguished from Si atoms by scanning tunneling spectroscopy and voltage dependent STM images, the growth mode of the added layer could be studied. On the (100) surface with a (2${\times}$1) reconstruction, Ge overlayer grow preferentially on the B type step edges at 720K. On the (111) surface, Ge overlayer also grow on the step edges with (7${\times}$7) and (5${\times}$5) structure depending on their coverage and annealing temperature.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.321-325
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• 2004

Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can be characterized by inappropriate and disorganized vessel. This paper present a method for blood vessel detection on infant retinal images. The algorithm is designed to detect the retinal vessels. The proposed method applies a Lapalacian of Gaussian as a step-edge detector based on the second-order directional derivative to identify locations of the edge of vessels with zero crossings. The procedure allows parameters computation in a fixed number of operations independent of kernel size. This method is composed of four steps : grayscale conversion, edge detection based on LOG, noise removal by adaptive Wiener filter & median filter, and Otsu's global thresholding. The algorithm has been tested on twenty infant retinal images. In cooperation with the Digital Imaging Research Centre, Kingston University, London and Department of Opthalmology, Imperial College London who supplied all the images used in this project. The algorithm has done well to detect small thin vessels, which are of interest in clinical practice.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.133-140
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• 2005

This paper introduces a spatial error concealment technique using directional interpolation in block-based compression. The first step involves finding the spatial direction vectors represented an edge-direction in the lost block using spatial boundary matching algorithm. Then, the error blocks are recovered by directional interpolation through these vectors and concealed by using the recovered blocks which have lower directional boundary matching error out of them relatively. This proposed method is able to deal with errors on macroblock or slice level adaptively. And it has lower complexity and maintains better performance compared to the conventional methods.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.281-284
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• 2003

In this study, we have proposed the method of moving area detection as the preprocessing step of moving object tracking system. First, we catch the two frames which are different at time in image sequence. We obtain the moving area by using their binary differential image. In differential image, the object area of previous and current frame is present. In the tracking system, the background is changed by camera motion. So, in this case we have to decide which moving area of object is current at time. We obtain the binary edge image of current frame by applying a threshold to the output of an edge detector. Then we performed logical AND operation between the edge image and differential image. As a result of this work moving area of object can be detected.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.77-82
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• 2017

In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.287-292
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• 2002

This paper presents a reverse engineering method for compound surfaces using vision system. A CNC machining center is used as a measuring station, which is equipped with slit beam generator and vision probe. Since obtained data using slit beam or laser scanner may have much data loss along the edge of compound surfaces, an algorithm is presented in this study to recover missing geometric data at such region. First, b-spline interpolation is applied to extract edge information of the surface, and as a next step, b-spline approximation is applied to recover the missing geometric data. Finally, b-spline skinning method is applied to regenerate the surface information. Appropriate simulation and experimental works are preformed to very the effectiveness of the proposed methods.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.2
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• pp.76-81
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• 2002

A numerical simulation of wake behavior behind three-dimensional wings in ground effect is done using an indirect boundary element method (Panel Method). An integral equation is obtained by applying Green's 2nd Identity on all surfaces of the flow domain. The AIC is constructed by imposing the no penetration condition on solid surfaces, and the Kutta at the wing's trailing edge. The ground effect is included using an image method. At each time step, a row of wake panels from wings' trailing edge are convected downstream following the force-free condition. The roll-up of wake vortices behind wings in close proximity is simulated.

• KIEAE Journal
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• v.3 no.2
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• pp.59-66
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• 2003

To be the design method supporting aesthetic ability of human, CAAD system should essentially recognize architectural form in the same way of human. In this study, visual perception process of human was analyzed to search proper computational method performing similar step of perception of it. Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate. This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence.