• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.375-382
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• 2003

Lip-reading technique based on bimodal is to enhance speech recognition rate in noisy environment. It is most important to detect the correct lip-image. But it is hard to estimate stable performance in dynamic environment, because of many factors to deteriorate Lip-reading's performance. There are illumination change, speaker's pronunciation habit, versatility of lips shape and rotation or size change of lips etc. In this paper, we propose the IIR filtering in time-domain for the stable performance. It is very proper to remove the noise of speech, to enhance performance of recognition by digital filtering in time domain. While the lip-reading technique in whole lip image makes data massive, the Principal Component Analysis of pre-process allows to reduce the data quantify by detection of feature without loss of image information. For the observation performance of speech recognition using only image information, we made an experiment on recognition after choosing 22 words in available car service. We used Hidden Markov Model by speech recognition algorithm to compare this words' recognition performance. As a result, while the recognition rate of lip-reading using PCA is 64%, Time-domain filter applied to lip-reading enhances recognition rate of 72.4%.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.6-6
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• 1996

컴퓨터 통신망의 활용이 각 분야에서 걸쳐서 점차 확대되고 있으며 의료 분야에서도 원격진료(tele-medicine), 원격교육(tele-education), 원격수술(tele-surgery) 등에 대한 시스템 개발이 관심을 끌고 있다. 본 연구에서는 초고속 정보통신망 환경에서 정형외과 모의수술을 하기 위한 시뮬레이터의 프로토타입을 구현하였다. 원격 모의수술 시뮬레이터를 구축하기 위해서는 CT, MRI와 같은 의학영상 처리, 다지점간의 회의를 제어할 수 있는 통신 제어, 환자의 진료를 위한 멀티미디어 데이터의 저장 및 검색을 위한 데이터베이스 구축 등 다양한 기술들의 총체적인 결합이 요구되어진다. 구축 시뮬레이터는 세가지 주요 서브 시스템으로 구성된다. 첫째, 원격 시뮬레이션을 위한 전반적인 관리, 운영, 제어를 담당하는 수술회의 시스템, 둘째, 모의수술을 가능케 하기 위한 2차원 영상의 전처리 3차원 영상 재구성 및 조작을 통한 모의수술 시스템, 셋재, 멀티미디어 환자 자료의 검색 및 관리를 하기 위한 데이터베이스 운영시스템으로 구성된다. 제안된 원격 모의수술 시뮬레이터는 서버-클라이언트 구조를 기반으로 하고, 여러명의 의사가 공동작업(CSCW: Computer Supported Cooperative Work)에 의해 모의수술을 할 수 있도록 공용 윈도우를 기반으로 한 그래픽 사용자 인터페이스를 제공한다. 멀티미디어 의료 데이터의 전송은 TCP/IP 프로토콜을 사용하고, 사용자 인터페이스는 X-window를 이용하여 구축하였다. 본 시뮬레이터는 SUN Server 1000을 서버로 하고, 두대의 SDT Workstation을 클라이언트로 하여 Ethernet 환경에서 구현 및 검증하였다. 또한 ATM Network에서 본 시뮬레이터를 시험함으로써 국책 사업으로 구축되는 초고속 정보통신망 환경에서의 사용 가능성을 입증하였다. 판단된다.원과 섭식장소, 수중생물의 경우는 특히 수온, 수량 영양원등이다.(중략). 본 연구의 접근방법으로는 ASRS의 개념적인 Reference Model을 수립하고 이 Reference Model에 대한 Formal Model로 DEVS(Discrete Event System Specification)을 이용하여 시스템을 Modeling하였다. 이의 Computer Simulation을 위하여 DEVS형식론 환경에서의 Simulation Language인 DEVSim ++ⓒ를 이용하여 시스템을 구현하였다.. 실형 결과로는 먼저 선형 상미분방정식의 예로 mass-damper-spring system, 비선형 상미분방정식의 예로는 van der Pol 방정식, 연립 상미분방정식의 예로는 mixing tank problem 등을 보였으며, 그의 공학에서 일어나는 여러 가지 문제들도 다루었다.화물에 대한 방어력이 증가되어 나타난 결과로 여겨지며, 또한 혈청중의 ALT, ALP 및 LDH활성을 유의성있게 감소시키므로서 감잎 phenolic compounds가 에탄올에 의한 간세포 손상에 대한 해독 및 보호작용이 있는 것으로 사료된다.반적으로 홍삼 제조시 내공의 발생은 제조공정에서 나타나는 경우가 많으며, 내백의 경우는 홍삼으로 가공되면서 발생하는 경우가 있고, 인삼이 성장될 때 부분적인 영양상태의 불충분이나 기후 등에 따른 영향을 받을 수 있기 때문에 앞으로 이에 대한 많은 연구가 이루어져야할 것으로 판단된다.태에도 불구하고 [-wh]의미의 겹의문사는 병렬적 관계의 합성어가 아니라 내부구조를 지니지 않은 단순한 단어(minimal $X^{0}$ elements)로 가정한다. 즉, [+wh] 의미의 겹의문사는 동일한 구성요 소를 지닌 병렬적 합성어([$[W1]_{XO-}$ $[W1]_{

• Journal of radiological science and technology
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• v.35 no.2
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• pp.133-139
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• 2012

For the examination of nuclear medicine, myocardial scan is a good method to evaluate a hemodynamic importance of coronary heart disease. but, the automatized qualitative measurement is additionally necessary to improve the decoding efficiency. we suggests the creation of cardiac three-dimensional model and model of three-dimensional cardiac thickness as a new measurement. For the experiment, cardiac reduced cross section was obtained from SPECT. Next, the pre-process was performed and image segmentation was fulfilled by level set. for the modeling of left cardiac thickness, it was realized by applying difference equation of two-dimensional laplace equation. As the result of experiment, it was successful to measure internal wall and external wall and three-dimensional modeling was realized by coordinate. and, with laplace formula, it was successful to develop the thickness of cardiac wall. through the three-dimensional model, defects were observed easily and position of lesion was grasped rapidly by the revolution of model. The model which was developed as the support index of decoding will provide decoding information to doctor additionally and reduce the rate of false diagnosis as well as play a great role for diagnosing IHD early.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.587-598
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• 2021

This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.437-456
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• 2021

In the field of remote sensing in Korea, starting in 2017, deep learning has begun to show efficient research results compared to existing research methods. Currently, research is being conducted to apply deep learning in almost all fields of remote sensing, from image preprocessing to applications. To analyze the research trend of deep learning applied to the remote sensing field, Korean domestic journal papers, published until October 2021, related to deep learning applied to the remote sensing field were collected. Based on the collected 60 papers, research trend analysis was performed while focusing on deep learning network purpose, remote sensing application field, and remote sensing image acquisition platform. In addition, open source data that can be effectively used to build training data for performing deep learning were summarized in the paper. Through this study, we presented the problems that need to be solved in order for deep learning to be established in the remote sensing field. Moreover, we intended to provide help in finding research directions for researchers to apply deep learning technology into the remote sensing field in the future.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Informatization Policy
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• v.31 no.1
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• pp.3-31
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• 2024

This study aimed to examine public concerns in South Korea considering the country's unique context, triggered by the advent of generative artificial intelligence such as ChatGPT. To achieve this, comments from 102 YouTube video news related to ethical issues were collected using a Python scraper, and morphological analysis and preprocessing were carried out using Textom on 15,735 comments. These comments were then analyzed using a Correlated Topic Model (CTM). The analysis identified six primary topics within the comments: "Legal and Ethical Considerations"; "Intellectual Property and Technology"; "Technological Advancement and the Future of Humanity"; "Potential of AI in Information Processing"; "Emotional Intelligence and Ethical Regulations in AI"; and "Human Imitation."Structuring these topics based on a correlation coefficient value of over 10% revealed 3 main categories: "Legal and Ethical Considerations"; "Issues Related to Data Generation by ChatGPT (Intellectual Property and Technology, Potential of AI in Information Processing, and Human Imitation)"; and "Fear for the Future of Humanity (Technological Advancement and the Future of Humanity, Emotional Intelligence, and Ethical Regulations in AI)."The study confirmed the coexistence of various concerns along with the growing interest in generative AI like ChatGPT, including worries specific to the historical and social context of South Korea. These findings suggest the need for national-level efforts to ensure data fairness.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.206-213
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• 2003

In this paper, we propose a design method of automatic thickness measurement and defect inspection system, which measures the thickness of the autoclaved lightweight concrete block and inspects the defect on a real-time basis. The image processing system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. For the realization of proposed algorithm, the preprocessing method that can be applied to overcome uneven lighting environment, threshold decision method, unit length decision method in uneven condition with rocking objects, and the curvature calibration method of camera using a constructed grid are developed. From the experimental results, we have found that the required measurement accuracy specification is sufficiently satisfied using our proposed method.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.37-44
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• 2013

In study suggested clinical availability to shoulder forced traction method in term of quality of image, the patient's convenience and stability, according to whether to use of shoulder forced traction bend using computed tomography(CT) that X-ray calibration and various mathematic calibration algorithm application can be applied by AEC. To achieve this, 79 patients is complaining of cervical pain oriented that shoulder forced traction bend use the before and after acquires lateral projection scout image and transverse image. transverse image of a fixed size in concern field of pixel and figure the average HU value compare that quantitative analysis. Artifact and pixel and resolution to qualitative clinical estimation image analysis. the patient feel inconvenience degree that self-diagnosis survey that estimate. As a result, lateral projection scout image if you used shoulder forced traction bend for the depicted has been an increase in the number of a cervical vertebrae. transverse image concern field shoulder forced traction bend use the before and after for pixel and the average HU-value changes was judged to be almost irrelevant. Artifact and resolution and contrast, in qualitative analysis of the results relating the observer to the unusual result. So, the patients of 82.27% complained discomfort that use of shoulder forced traction bend in self-diagnosis survey. No merit of medical image by using of bend from result was analyzed quality of image to quantitative and qualitative method judged. Nowadays, CT is supplied possible revision of quality of radiation by reduction of slice and automatic exposure controller, etc and application of preconditioning filter process due to various mathematic revision algorithm. So, image noise by beam hardening artifact should not be a problem. shoulder forced traction bend of use no longer judged clinically availability because have not influence of image quality and give discomfort, have extra dangerousness.