• Journal of Korean Library and Information Science Society
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• v.47 no.3
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• pp.21-39
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• 2016

The objective of this study is to propose the operational organization and connective cooperation plan for the Daegu regional central library which will be completed in 2020. The vision of regional central library was presented as 'the library for the happiness of Daegu citizens and the cradle of knowledge and culture', and 10 core functions also proposed. In order to fulfill the roles as a regional central library, it has been suggested to maintain 5 departments including the department of administrative support, the department of library policy, the department of collection development, the department of information service, and the department of cooperative preservation. Lastly, it has also established the model of connective cooperation plans between other regional libraries and the regional central library as follows: the construction and operation of cooperative system, connective cooperation for the construction of Daegu collaborative repository, cooperative library system of ILL/DDS.

• 전자공학회논문지 IE
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• v.44 no.4
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• pp.48-54
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• 2007

Due to the diverse utilization of multimedia, interests are increasing towards processing (saving, editing, searching, etc) three dimensional object data. This paper proposes and realizes a retrieval system for three dimensional objects using reflective symmetry. For the retrieval method, a reflective symmetric axis with a projector is used. The symmetric plane is calculated by the reflection symmetry, and the depth buffer is calculated for the symmetric plane. Then, by applying the Fourier Transform to the depth buffer, the feature vector for the object is generated and retrieved. For the sample of inquiry, the model of similar symmetry was extracted using the benchmark data from Konstantz University. Considering that most of the objects have symmetrical characteristics, the proposed method of retrieving three dimensional objects using a reflective symmetric surface is an outstanding retrieval system.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.279-287
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• 2006

This paper proposes a method to detect fall action by using stereo images to recognize emergency situation. It uses 3D information to extract the visual information for learning and testing. It uses HMM(Hidden Markov Model) as a recognition algorithm. The proposed system extracts background images from two camera images. It extracts a moving object from input video sequence by using the difference between input image and background image. After that, it finds the bounding rectangle of the moving object and extracts 3D information by using calibration data of the two cameras. We experimented to the recognition rate of fall action with the variation of rectangle width and height and that of 3D location of the rectangle center point. Experimental results show that the variation of 3D location of the center point achieves the higher recognition rate than the variation of width and height.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.93-96
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• 2015

In this paper, we introduce a fire detection system using context-aware sensor. In existing weather and based on vision sensor of fire detection system case, acquired image through sensor of camera is extracting features about fire range as processing to convert HSI(Hue, Saturation, Intensity) model HSI which is color space can have durability in illumination changes. However, in this case, until a fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. Additionally, the fire detection in complex situations as well as difficult to separate continuous boundary is set for the required area is difficult. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire it. In addition, it is possible to differential management to intensive fire detection is required zone dividing the state of fire.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1313-1324
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• 2014

Korea has high quality level of ICT Technologies, however it still have a long way to go before invigoration of ICT in agriculture industry. The government of Korea supply to agriculture ICT systems, however these are the enclosed type and insufficient the level of connectivity, compatibility, and integrity between ICT systems. Farmers can not share crop information and one system can not use with others in combination. Recently, IoT(Internet of Things) become popular to emphasize the vision of a global internet and ICT industry. The IoT is a critical technology that leads future internet generation. We believe that IoT will change status of agriculture industry and appearance of various agriculture business model. Using IoT technology is provided a platform of opportunities to optimize work processes and efficient use of energy, time and labour in farm. It can automatically control temperature, humidity, sunshine system and so on for optimal growth conditions at greenhouse and plant factory. Growth setting can even be controlled and monitored crop condition and disease by a smartphone app or PC. It is possible to improve quality of farming and farm product. We suggest that construction of IoT platform through open API in agriculture industry.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.21-27
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• 2002

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three-dimensional surfaces. However, those conventional visual or optical methods have inherent shortcomings such as occlusion and variant surface reflection. X-ray vision system can be a good solution to these conventional problems, since we can extract the volume information including both the surface geometry and the inner structure of any objects. In the x-ray system, the surface condition of an object, whether it is lambertian or specular, does not affect the inherent characteristics of its x-ray images. In this paper, we propose a three-dimensional x-ray imaging method to reconstruct a three dimensional structure of an object out of two dimensional x-ray image sets. To achieve this by the proposed method, two or more x-ray images projected from different views are needed. Once these images are acquired, the simultaneous algebraic reconstruction technique(SART) is usually utilized. Since the existing SART algorithms have several shortcomings such as low performance in convergence and different convergence within the reconstruction volume of interest, an advanced SART algorithm named as USART(uniform SART) is proposed to avoid such shortcomings and improve the reconstruction performance. Because, each voxel within the volume is equally weighted to update instantaneous value of its internal density, it can achieve uniform convergence property of the reconstructed volume. The algorithm is simulated on various shapes of objects such as a pyramid, a hemisphere and a BGA model. Based on simulation results the performance of the proposed method is compared with that of the conventional SART method.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.47-54
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• 2018

The purpose of this study is to verify the long - range measurement performance for practical field application of VDMS. The reliability of the VDMS was verified by comparison with the existing monitoring sensor, GPS, Accelerometer and LDS. It showed the ability to accurately measure the dynamic displacement by tracking a motion of free vibration of target. And using the PSD function of measured data, the results in the frequency domain were also analyzed. We judged that VDMS is able to identify the higher system mode and has sufficient reliability. Based on the reliability verification, we conducted tests for long-distance applicability for actual application of VDMS. The distance from the stationary target model structure was increased by 50m interval, and the maximum distance was set to 400m. From the distance of 150m, the image obtained by the commercial camcorder has an error in the analysis, so the measured displacement comparison was performed between the LDS and the refractor telescope measurement results. In the measurement results of the displacement area of VDMS, the data validity was deteriorated due to the data shift by the external force and the quality degradation of the enlarged image. However, even under the condition that the effectiveness of the displacement measurement data of VDMS is low, the first mode characteristic included in the free vibration of the object is clearly measured. If the influence from the external environment is controlled and stable data is collected, It is judged that reliability of long-distance VDMS can be secured.

• Journal of IKEEE
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• v.24 no.4
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• pp.1141-1147
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• 2020

The hornet species are so similar in shape that they are difficult for non-experts to classify, and because the size of the objects is small and move fast, it is more difficult to detect and classify the species in real time. In this paper, we developed a system that classifies hornets species in real time based on a deep learning algorithm using a boundary box. In order to minimize the background area included in the bounding box when labeling the training image, we propose a method of selecting only the head and body of the hornet. It also experimentally compares existing boundary box-based object recognition algorithms to find the best algorithms that can detect wasps in real time and classify their species. As a result of the experiment, when the mish function was applied as the activation function of the convolution layer and the hornet images were tested using the YOLOv4 model with the Spatial Attention Module (SAM) applied before the object detection block, the average precision was 97.89% and the average recall was 98.69%.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.71-83
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• 2020

In this paper, we propose a system that can detect the shape of a hand at high speed using an FPGA. The hand-shape detection system is designed using Verilog HDL, a hardware language that can process in parallel instead of sequentially running C++ because real-time processing is important. There are several methods for hand gesture recognition, but the image processing method is used. Since the human eye is sensitive to brightness, the YCbCr color model was selected among various color expression methods to obtain a result that is less affected by lighting. For the CbCr elements, only the components corresponding to the skin color are filtered out from the input image by utilizing the restriction conditions. In order to increase the speed of object recognition, a median filter that removes noise present in the input image is used, and this filter is designed to allow comparison of values and extraction of intermediate values at the same time to reduce the amount of computation. For parallel processing, it is designed to locate the centerline of the hand during scanning and sorting the stored data. The line with the highest count is selected as the center line of the hand, and the size of the hand is determined based on the count, and the hand and arm parts are separated. The designed hardware circuit satisfied the target operating frequency and the number of gates.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.31-38
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• 2009

Lens distortion is inevitable phenomenon in machine vision system. More and more distortion phenomenon is occurring in order to choice of lens for minimizing cost and system size. As shown above, correction of lens distortion is critical issue. However previous lens correction methods using camera model have problem such as nonlinear property and complicated operation. And recent lens correction methods using neural network also have accuracy and efficiency problem. In this study, I propose new algorithms for correction of lens distortion. Distorted image is divided based on the distortion quantity using k-means. And each divided image region is corrected by using neural network. As a result, the proposed algorithms have better accuracy than previous methods without image division.