• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.133-139
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• 2004

In this paper. we propose a medical image processing method for detection of periodontal disease by geometric analysis on dental digital radiography. This paper proposes the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by image processing technique, that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the geometric features in target images. Therefore, we use these methods because they give accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.3
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• pp.63-70
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• 2020

Two rotational motions of the 5-axis machine tool maximize the degree of freedom of the tool axis vector, which improves tool accessibility; however, this lowers feed speed and rigidity, which impairs machining stability. In addition, cutting efficiency is lowered when compared with a flat end mill because typically, the ball-end mill is used when machining by rotational motion. This study increased cutting efficiency by using a corner radius flat end mill during impeller roughing. Furthermore, we proposed a fixed controlled machining of the rotary motion using geometric shape information to improve the feed speed and machining stability. Finally, we proposed a finishing tool path generation method using a vector net to increase the convenience and practicality of tool path generation. To verify its effectiveness, we compared the machining time, shape accuracy, and surface quality of the proposed method and an existing dedicated module.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.12
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• pp.1465-1474
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• 1992

This paper describes a new overlapped object recognition method using extended local features. At first, we extract the extended local features consisting of corners, arcs, parallel-lines, and corner-arcs from the images consisting of model objects. Based on the extended local features we construct a knowledge-base. In order to match objects, we also extract the extended local features from the input image, and then check the compatibility between the extracted features and the features in the knowledge-base. From the set of compatible features, we compute geometric transforms. If any geometric transforms are clustered, we generate the hypothesis of the objects as the centers of the clusters, and then verify the hypothesis by a reverse geometric transform. An experiment shows that the proposed method increases the recognition rate and the accuracy as compared with existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6190-6213
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• 2019

For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.133-160
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• 1994

In this paper, we propose a comprehensive geometric correction algorithm of Along Track Scanning Radiometer(ATSR) images. The procedure consists of two cascaded modules; precorrection and fine co-location. The pre-correction algorithm is based on the navigation model which was derived in mathematical forms. This model was applied for correction raw(un-geolocated) ATSR images. The non-systematic geometric errors are also introduced as the limitation of the geometric correction by this analytical method. A fast and automatic algorithm is also presented in the paper for co-locating nadir and forward views of the ATSR images by using a binary cross-correlation matching technique. It removes small non-systematic errors which cannot be corrected by the analytic method. The proposed algorithm does not require any auxiliary informations, or a priori processing and avoiding the imperfect co-registratio problem observed with multiple channels. Coastlines in images are detected by a ragion segmentation and an automatic thresholding technique. The matching procedure is carried out with binaty coastline images (nadir and forward), and it gives comparable accuracy and faster processing than a patch based matching technique. This technique automatically reduces non-systematic errors between two views to .$\pm$ 1 pixel.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.521-529
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• 2019

Interlocked armor layers of unbonded flexible risers may crush when risers are being launched. In order to predict the behavior of interlocked armor layers, they are usually simplified as rings with geometric and contact nonlinearity ignored in the open-literature. However, the equivalent thickness of the interlocked armor layer has not been addressed yet. In the present paper, a geometric coefficient ${\gamma}$ is introduced to the equivalent stiffness method, and a linear relationship between ${\gamma}$ and geometric parameters of interlocked armor layers is validated by analytical and finite element models. Radial stiffness and equivalent thickness of interlocked armor layers are compared with experiments and different equivalent methods, which show that the present method has a higher accuracy. Furthermore, hoop stress distribution of interlocked armor layer under crushing is predicted, which indicates the interlocked armor layer can be divided into two compression and two expansion zones by four symmetrically distributed singular points.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.752-759
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• 2022

The instantiation of spaces as a discrete entity allows users to utilize BIM models in a wide range of analyses. However, in practice, their utility has been limited as spaces are erroneously entered due to human error and often omitted entirely. Recent studies attempted to automate space allocation using artificial intelligence approaches. However, there has been limited success as most studies focused solely on the use of geometric features to distinguish spaces. In this study, in addition to geometric features, semantic relations between spaces and elements were modeled and used to improve space classification in BIM models. Graph Convolutional Networks (GCN), a deep learning algorithm specifically tailored for learning in graphs, was deployed to classify spaces via a similarity graph that represents the relationships between spaces and their surrounding elements. Results confirmed that accuracy (ACC) was +0.08 higher than the baseline model in which only geometric information was used. Most notably, GCN was able to correctly distinguish spaces with no apparent difference in geometry by discriminating the specific elements that were provided by the similarity graph.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.180-188
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• 1994

Error assessment and evaluation for machine for machine tool slides have been considered as essential tools for improving accuracy. In this paper, a computer aided measurement technique is proposed using photo pin diodes of quadrant type and laser source. In thedeveloped system, three photo diodes are mounted on a sensor mounting table, and the sensored signal is processed by specially designed signal conditioner to give fine resolution with minimum noise. A micro computer inputs the processed signal, and the geometric errors of five degree of freedoms are successfully evaluated. Pitch, roll, yaw, vertical and horizontal straightness errors are thus assessed simultaneously for a machine tool slide. Calibration techniques such as optics calibration, photo diode calibration are proposed and implemented, giving precise calibration for the measurement system. The developed system has been applied to a practical machine tool slide, and has been found as one of efficient and precise technique for machine tool slide.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.344-346
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• 2004

IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.