• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.606-611
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• 2009

This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred impression on users. Physical parameters of the 3D objects that might strongly contribute to their visual impressions are sought through computational investigation of the impression ratings obtained for learning samples. "Car body" was selected as the class of 3D objects to be investigated. A morphable 3D model of car bodies that describes the variations in appearance using a smaller number of parameters was obtained. Based on each car body's rating for the impression of speediness obtained by paired comparison, the visual impression was transformed by manipulating the parameters defined in the morphable 3D model. The validity of the proposed method was confirmed by psychological experiments. A new scheme is also proposed to properly re-sample a novel object of a peculiar shape so that such an object could also be represented by the morphable 3D model.

• Journal of IKEEE
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• v.24 no.1
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• pp.200-207
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• 2020

In this paper, an area-efficient feature extractor was proposed for security surveillance radar systems and FPGA-based implementation results were presented. In order to reduce the memory requirements, features extracted from Doppler profile for FFT window-size are used, while those extracted from total spectrogram for frame-size are excluded. The proposed feature extractor was design using Verilog-HDL and implemented with Xilinx Zynq-7000 FPGA device. Implementation results show that the proposed design can reduce the logic slice and memory requirements by 58.3% and 98.3%, respectively, compared with the existing research. In addition, security surveillance radar system with the proposed feature extractor was implemented and experiments to classify car, bicycle, human and kickboard were performed. It is confirmed from these experiments that the accuracy of classification is 93.4%.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1030-1036
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• 2006

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on the feature values, the use pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function considering weighted feature values. The performance of our scheme is evaluated by a simulation. Simulation results demonstrate that the anomalies are well detected by the method that assigns different weighted values to feature attributes depending on importance.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.276-285
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• 1997

Engineers need to reduce the product design time interval and deal with frequent design changes. For this purpose a design expert system has been developed where a 3D CAD system is used for the visualization of a design layout especially the car audio design. This expert system is based on the configuration design methodology, one of the design methods which emulates the engineering design process, and the parametric design method. The design methods and heuristic knowledge are represented as rules, and design parts are represented as objects with properties. After an inference process, design parameters are extracted and they are used leer the parametric design. This study focused on the shape visualization of product components in the preliminary design phase.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1486-1495
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• 2018

This paper investigates the autonomous ground vehicle (AGV) localization filter design problem under GNSS-denied environments. It is assumed that the given landmarks do not have unique features due to the lack of a prior knowledge on them. For such case, the AGV may have difficulties in distinguishing the position measurement of the detected landmark from those of other landmarks with the same feature, hence the conventional localization filters are not applicable. To resolve this technical issue, the localization filter design problem is formulated as a special form of the data association determining whether the detected feature is actually originated from which landmark. The measurement hypotheses generated by landmarks with the same feature are evaluated by the nearest neighbor data association scheme to reduce the computational burden. The position measurement corresponding to the landmark with the most probable hypothesis is used for localization filter. Through the experiments in real-driving condition, it is shown that the proposed method provides satisfactory localization performance in spite of using non-unique landmarks.

• Journal of Platform Technology
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• v.6 no.4
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• pp.26-33
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• 2018

In this paper, we propose an image retrieval algorithm for real-time processing and design it as hardware. The proposed method is based on the classification of BoWs(Bag of Words) algorithm and proposes an image search algorithm using bit stream. K-fold cross validation is used for the verification of the algorithm. Data is classified into seven classes, each class has seven images and a total of 49 images are tested. The test has two kinds of accuracy measurement and speed measurement. The accuracy of the image classification was 86.2% for the BoWs algorithm and 83.7% the proposed hardware-accelerated software implementation algorithm, and the BoWs algorithm was 2.5% higher. The image retrieval processing speed of BoWs is 7.89s and our algorithm is 1.55s. Our algorithm is 5.09 times faster than BoWs algorithm. The algorithm is largely divided into software and hardware parts. In the software structure, C-language is used. The Scale Invariant Feature Transform algorithm is used to extract feature points that are invariant to size and rotation from the image. Bit streams are generated from the extracted feature point. In the hardware architecture, the proposed image retrieval algorithm is written in Verilog HDL and designed and verified by FPGA and Design Compiler. The generated bit streams are stored, the clustering step is performed, and a searcher image databases or an input image databases are generated and matched. Using the proposed algorithm, we can improve convenience and satisfaction of the user in terms of speed if we search using database matching method which represents each object.

• Journal of the Korean Society of Costume
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• v.56 no.7 s.106
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• pp.148-162
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• 2006

The purpose of this study is to examine the concept of convergence which is one of the trendy issues as a new digital paradigm of Integrative thinking in 21st century, to analyze the plastic feature and internal meaning of convergence expressed in fashion design, and to grasp the cultural symbolism through this aesthetic analysis. Because there have been considerable discussions on convergence, centering on industrial product area associated with media, I will proceed my study on the basis of them. For this, the documentary study and practical case study have been executed. This study will be helpful to find a direction of future fashion design trend. Convergence in digital stage can be defined as a phenomenon which different functions of product move towards one direction for greater efficiency, and not only as a technical integration between functions of product, but also an extension of area. Convergence can be classified by their use as (1) convergence for convenient daily life (2) convergence with intelligent scientific technology (3) convergence for entertainment on the basis of sensual experience. The plasticity of convergence designs feature as a open dynamic structure which potentiate transformation and their internal meaning can be inquired such qualities as integrative multiplicity, efficiency, mobility, intelligence. Specially convergence fashion design has protection qualify resulting from wearability on body. Ultimately convergence fashion design as a future digital paradigm can be thought as both eco-friendly design and human-centered design from positive technology-based viewpoint, because it is easy to transform according to our environment, convenient to reserve, and efficient to enhance spatial usibility.

• Korean Journal of Computational Design and Engineering
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• v.8 no.3
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• pp.184-188
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• 2003

The harness design process consists of repetitious routines to decide the wire configuration in its interior. A slight change in one of the wire's configuration will require a total reconfiguration of the entire wire system. Therefore, the harness design is extremely time consuming and is vulnerable to human errors by an engineer. Based on both electrical and mechanical area, Wiring Harness system is in complicated area. Existing systems are, therefore, not exactly suitable for practical use. This paper presents a novel framework for ameliorating existing system's defects. In this paper, Visio and Visual Basic was interfaced to process wire bundle information and wire bundle location to alleviate problems mentioned beforehand concerning harness design; at the same time developing the automation of the entire design process based on the feature based design method, optional print, and management of documents for reuse.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.379-383
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• 2015

This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.161-177
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• 2016

In history based parametric CAD modeling systems, persistent identification of the topological entities after design modification is mandatory to keep the design intent by recording model creation history and modification history. Persistent identification of geometric and topological entities is necessary in the product design phase as well as in the re-evaluation stage. For the identification, entities should be named first according to the methodology which will be applicable for all the entities unconditionally. After successive feature operations on a part body, topology based persistent identification mechanism generates ambiguity problem that usually stems from topology splitting and topology merging. Solving the ambiguity problem needs a complex method which is a combination of topology and geometry. Topology is used to assign the basic name to the entities. And geometry is used for the ambiguity solving between the entities. In the macro parametrics approach of iCAD lab of KAIST a topology based persistent identification mechanism is applied which will solve the ambiguity problem arising from topology splitting and also in case of topology merging. Here, a method is proposed where no geometry comparison is necessary for topology merging. The present research is focused on the enhancement of the persistent identification schema for the support of ambiguity problem especially of topology splitting problem and topology merging problem. It also focused on basic naming of pattern features.