• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.6-12
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• 2009

In this paper, we propose a system that extracts licence plate and recognizes numerals in the licence plate. The candidate area of licence plate is extracted using the improved IAFC(Integrated Adaptive Fuzzy Clustering) fuzzy neural network. And the morphological filters are used to reduce noise from the extracted licence plate. The extracted licence plate is standardized using Hough transform and geometric transform. Backpropagation neural network is used to recognize numerals that are separated using the projection technique.

• Journal of IKEEE
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• v.23 no.1
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• pp.249-253
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• 2019

Most of music-transcription systems that have been commercialized operate based on audio information. However, these conventional systems have disadvantages of environmental dependency, equipment dependency, and time latency. This paper studied a vision-based music-transcription system that utilizes video information rather than audio information, which is a traditional method of music-transcription programs. Computer vision technology is widely used as a field for analyzing and applying information from equipment such as cameras. In this paper, we created a program to generate MIDI file which is electronic music notes by using smart-phone cameras to record the play of piano.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.39-40
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• 2022

최근 전동 킥보드, 전동휠, 전기 자전거 등 개인형 이동수단(Personal Mobility)의 보급이 늘면서 관련 인명 교통사고가 급증하고 있다. 본 논문에서는 개인형 이동수단의 사용위험 및 사고 감소를 목적으로, 딥러닝 객체탐지 기술을 적용하여 다양한 위험요소를 증강현실 기술을 기반으로 한 HMD(Helmet mounted display)에 표시하는 '딥러닝 객체 인식과 증강현실을 적용한 개인 이동장치를 위한 HMD(Helmet Mounted Display) 어플리케이션'을 설계한다. 제시하는 방법은 실시간으로 수집된 전방의 실시간 영상 정보를 객체 탐지 알고리즘을 통해 위험요소 및 안전한 주행을 보조하는 객체를 감지하고 증강현실을 적용해 사용자에게 적절한 운전 보조장치 및 기능을 제공한다.

• Korean Journal of Optics and Photonics
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• v.29 no.1
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• pp.19-27
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• 2018

A change in object distance would generally change the magnification of an optical system. In this paper, we have proposed and designed a double-Gauss optical system with a fixed magnification and image surface regardless of any change in object distance, according to moving the lens groups a little bit to the front and rear of the stop, independently parallel to the direction of the optical axis. By maintaining a constant size of image formation in spite of various object-distance changes in a projection system such as a head-up display (HUD) or head-mounted display (HMD), we can prevent the field of view from changing while focusing in an HUD or HMD. Also, to check precisely the state of the wiring that connects semiconductor chips and IC circuit boards, we can keep the magnification of the optical system constant, even when the object distance changes due to vertical movement along the optical axis of a testing device. Additionally, if we use this double-Gauss optical system as a vision system in the testing process of lots of electronic boards in a manufacturing system, since we can systematically eliminate additional image processing for visual enhancement of image quality, we can dramatically reduce the testing time for a fast test process. Also, the Gaussian bracket method was used to find the moving distance of each group, to achieve the desired specifications and fix magnification and image surface simultaneously. After the initial design, the optimization of the optical system was performed using the Synopsys optical design software.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.671-680
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• 2021

This paper deals with the contents of designing and producing reconnaissance hardware and software, and verifying the functions after being installed on the CanSat platform and ground stations. The main reconnaissance mission is largely composed of two things: terrain search that renders the surrounding terrain in 3D using radar, GPS, and IMU sensors, and real-time detection of major objects through optical camera image analysis. In addition, data analysis efficiency was improved through GUI software to enhance the completeness of the CanSat system. Specifically, software that can check terrain information and object detection information in real time at the ground station was produced, and mission failure was prevented through abnormal packet exception processing and system initialization functions. Communication through LTE and AWS server was used as the main channel, and ZigBee was used as the auxiliary channel. The completed CanSat was tested for air fall using a rocket launch method and a drone mount method. In experimental results, the terrain search and object detection performance was excellent, and all the results were processed in real-time and then successfully displayed on the ground station software.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.3
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• pp.112-121
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• 2020

In suspension bridges, hanger cables are the main load-supporting members. The tension of the hanger cables of a suspension bridge is a very important parameter for assessing the integrity and safety of the bridge. In general, indirect methods are used to measure the tension of the hanger cables of a suspension bridge in traffic use. A representative indirect method is the vibration method, which extracts modal frequencies from the cables' responses and then measures the cable tension using the cables' geometric conditions and the modal frequencies. In this study, the image processing technique is applied to facilitate the estimation of the dynamic responses of the cables using the image signal, for which a portable digital camcorder was used due to its convenience and cost-efficiency. Ambient vibration tests were conducted on a suspension bridge in traffic use to verify the validity of the back analysis method, which can estimate the tension of remote hanger cables using the modal frequencies as a parameter. In addition, the tension estimated through back analysis method, which was conducted to minimize the difference between the modal frequencies calculated using finite element analysis of the hanger cables and the measured modal frequencies, was compared with that measured using the vibration method.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.21 no.2
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• pp.249-259
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• 1991

The purpose of this study was to evaluate the incidence and radiographic features of 677 cases of hypercementosis by means of the analysis of full mouth periapical radiograms in 4,236 persons visited the Department of Oral Radiology, School of Dentistry, Kyung Hee University during January 1984 to December 1989. The obtained results were as follows: 1. The incidence of hypercementosis was revealed to be 8.2% in total examined persons, and there was a higher incidence in females (9.4%) than in males (7.1%). 2. The hypercementosis was most frequently occurred in the 6th decades (29.2%), and the incidence was increased by advancing age until 6th decades. 3. There was a higher incidence in the maxilla (59.5%) than in the mandible (40.5%), and maxillary second premolar (18.5%) was the most frequently involved tooth. The maxillary first premolar (11.7%) was next in order to frequency followed by maxillary canine (10.0%) and mandibular first and second premolars (9.6%). 4. In the etiologic factors, 35.0% were inflammation, 31.2% were elongation, 6.2% were trauma from occlusion, 0.1 % were uneruption, and 27.5% were unknown. 5. In the degree of cementum apposition, 35.3% were Type Ⅰ, 29.5% were Type Ⅱ, and 35.2% were Type Ⅲ. 6. In the status of cementum apposition, 3.2% were mesial side, 8.9% were distal side, and 87.9% were mesial & distal side. 7. In the identification of radiographic density between normal cementum and excessive cementum, 12.7% could be identified, and 87.3% could be unidentified.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.75-82
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• 2017

Recently, as the roles and utilization fields of UAV become more diverse, demand for high - level mission has been increasing. To solve this issue, researches on the operation of multiple small UAVs and related systems have been actively carried out. The multiple small UAVs based application system has a problem that the task complexity of control personnel increases because the control personnel must continuously control and manage several small UAVs. Hence, it is necessary to develop a software platform that can perform efficient control in order to employ a multiple small UAVs based application system successfully. In this paper, we propose an effective ground control software platform for application systems using multiple small UAVs. We first analyze the requirements for the software platform, and design and implement software based on the analysis. Simulation using the X-plane flight simulator shows that multiple flight data are effectively displayed and that the image data transmitted from many small UAVs are simultaneously displayed in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1314-1319
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• 2018

The current TW3 - based maximum height prediction technique used in KMAA(Korean Medical Academy of Auxology) is manual and subjective, and it requires a lot of time and effort in the medical treatment, while the interest in the child's growth is very high. In addition, the technique of classifying images using deep learning, especially convolutional neural networks, is used in many fields at a more accurate level than the human eyes, also there is no exception in the medical field. In this paper, we introduce a TW3 algorithm using deep learning, that uses the convolutional neural network to predict the growth level of the left hand bone, to predict the maximum height of child and youth in order to increase the reliability of predictions and improve the convenience of the doctor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.380-382
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• 2021

According to the National Police Agency, 161 out of 38,496 unsolved cases as of 2020. Most of the adult missing persons, the highest of the unsolved causes, are evaluated as simple runaway, which takes a long time to investigate. Even if search through CCTV, it can take a long time and the accuracy can be somewhat low because you have to check the faces of the characters one by one and find the characters only with the characteristics of the statements. This paper utilizes MTCNN to conduct research on character extraction in CCTV. We initiate simultaneous analysis of the features of faces learned with MTCNN and the clothes we are wearing, so that only the overlapping characters are extracted so that they can be identified to the related parties. For aim to learn more diverse feature detection to narrow down the features of missing persons in the future and increase their accuracy.