• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.77-80
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• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.688-693
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• 2010

Vision based object recognition in mobile robots has many issues for image analysis problems with neighboring elements in dynamic environments. SURF(Speeded Up Robust Features) is the local feature extraction method of the image and its performance is constant even if disturbances, such as lighting, scale change and rotation, exist. However, it has a difficulty of real-time processing caused by representation of high dimensional vectors. To solve th problem, execution of SURF in GPU(Graphics Processing Unit) is proposed and implemented using CUDA of NVIDIA. Comparisons of recognition rates and processing time for SURF between CPU and GPU by variation of robot velocity and image sizes is experimented.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.4
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• pp.189-203
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• 2014

In this study, Creative motifs using face composition of Jogakbo and Knot Symbol were developed, and applied to traditional Baeja of Joseon Dynasty to develop design contents of traditional clothes. As for study method, 7 motifs of new formative image that integrates traditional beauty and contemporary sense were developed by applying Knot Symbols and face compositions of Jogakbo with the use of Adobe Illustrator CS6 and Adobe Photoshop CS6 vector graphic software. The motifs were designed in contemporary image in face compositions like rectangle pattern, triangle pattern, dual rectangle pattern, vertical and horizontal pattern, pinwheel pattern, gojunmun pattern and free pattern by involving various changes like repetition, rotation, reduction, expansion and decomposition and using the colors used in the Jogakbo. It is desired that through this study, traditional Baeja may develop to bear traditional and contemporary image so that our traditional clothes design may become global. Also it is anticipated that this study will contribute to development of culture products of Hanbok like Jeogori, pants and skirt that require change of design in the global era while maintaining traditional beauty to appeal to the emotions of world citizens.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.96-105
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• 2004

The recovering 3D image from 2D requires the depth information for each picture element. The manual creation of those 3D models is time consuming and expensive. The goal in this paper is to estimate the relative depth information of every region from single view image with camera translation. The paper is based on the fact that the motion of every point within image which taken from camera translation depends on the depth. Motion vector using full-search motion estimation is compensated for camera rotation and zooming. We have developed a framework that estimates the average frame depth by analyzing motion vector and then calculates relative depth of region to average frame depth. Simulation results show that the depth of region belongs to a near or far object is consistent accord with relative depth that man recognizes.

• Journal of Sensor Science and Technology
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• v.17 no.5
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• pp.338-345
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• 2008

Steel bearing balls are important component in machines having moving parts. In this paper we describe a vision-based automatic inspection system designed for sensing defects on the surface of steel bearing balls. The system has a camera looking down over a rail on which balls roll. Two mirrors are installed at both sides of the rail so that the side parts of a ball can be well inspected. The entire ball surface can be sufficiently seen by taking three images at $120^{\circ}$ rotation interval. Defects are detected by thresholding the difference image between an image captured and the reference image of a good ball.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.782-788
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• 2018

This paper proposes a novel method for the omnidirectional camera-based image rendering synchronization system using head mounted display. There are two main processes in the proposed system. The first one is rendering 360-degree images which are remotely photographed to head mounted display. This method is based on transmission control protocol/internet protocol(TCP/IP), and the sequential images are rapidly captured and transmitted to the server using TCP/IP protocol with the byte array data format. Then, the server collects the byte array data, and make them into images. Finally, the observer can see them while wearing head mounted display. The second process is displaying the specific region by detecting the user's head rotation. After extracting the user's head Euler angles from head mounted display's inertial measurement units sensor, the proposed system display the region based on these angles. In the experimental results, rendering the original image at the same resolution in a given network environment causes loss of frame rate, and rendering at the same frame rate results in loss of resolution. Therefore, it is necessary to select optimal parameters considering environmental requirements.

• Smart Structures and Systems
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• v.24 no.5
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• pp.607-616
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• 2019

The video deflectometer based on digital image correlation is a non-contacting optical measurement method which has become a useful tool for characterization of the vertical deflections of large structures. In this study, a novel imaging model has been established which considers the variations of pitch angles in the full image. The new model allows deflection measurement at a wide working distance with high accuracy. A monocular video deflectometer has been accordingly developed with an inclination sensor, which facilitates dynamic determination of the orientations and rotation of the optical axis of the camera. This layout has advantages over the video deflectometers based on theodolites with respect to convenience. Experiments have been presented to show the accuracy of the new imaging model and the performance of the monocular video deflectometer in outdoor applications. Finally, this equipment has been applied to the measurement of the vertical deflection of Yingwuzhou Yangtze River Bridge in real time at a distance of hundreds of meters. The results show good agreement with the embedded GPS outputs.

• ETRI Journal
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• v.43 no.4
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.505-507
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• 2021

Image recognition technology is a technology that recognizes an image object by using the generated feature descriptor and generates object feature points and feature descriptors that can compensate for the shape of the object to be recognized based on artificial intelligence technology, environmental changes around the object, and the deterioration of recognition ability by object rotation. The purpose of the present invention is to implement a power management framework required to increase profits and minimize damage to livestock farmers by preventing accidents that may occur due to the improvement of efficiency of the use of livestock house power and overloading of electricity by integrating and managing a power fire management device installed for analyzing a complex environment of power consumption and fire occurrence in a smart safety livestock house, and to develop and disseminate a safe and optimized intelligent smart safety livestock house.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.95-105
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• 2006

This paper proposes a novel approach to represent the image by using shape descriptor having an information of area. The proposed descriptor is a set of vectors, consists of radius, area and direction parameters in the concentrated center point. Due to the area parameter, we know our descriptor can obtain the information of area. Also, we give an extended shape descriptor to get more detailed representation. To do this, we move the center point of our vision to that point for region of interest. By doing so about all of region of interest, we can get our descriptor for detailed information of the image. From more detailed descriptor, it's natural that it's more efficient fur representation, retrievals and so on. We make it the normalized pattern and expand to improve its quality. The proposed method is invariant to scale, position and rotation. The results show that it can be used efficiently for image representation as we can see in retrievals of silhouette images.