• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.254-258
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• 1996

In this paper, we proposed realtime visual tracking system of moving object for 2D target using extended Kalman Filter Algorithm. A targeting marker are recongnized in each image frame and positions of targer object in each frame from a CCD camera while te targeting marker is attached to the tip of the SCARA robot hand. After the detection of a target coming into any position of the field-of-view, the target is tracked and always made to be located at the center of target window. Then, we can track the moving object which moved in inter-frames. The experimental results show the effectiveness of the Kalman filter algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1583-1588
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• 2013

According to 2008 statistics, there is a need for sailing lookout to minimize the ships collision that caused a secondary damage such as environment pollution and it happened 25 percentage rate. The aim of this study is to construct the object targeting system for notifying the sailing and ship information as monitoring the marine with CCTV having a zoom, rotation, and tile function. In this study we expected to induce the safety sailing by offering the CCTV automatic treatment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.161-163
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• 2011

최근 몇 년사이 CCTV에 대한 활용도와 중요성이 대두되고 있으며, CCTV의 해상도 또한 SD급 CCTV에서 HD급 CCTV로 대부분 전환되고 있는 상황이다. HD급 CCTV는 고화질, 고해상도를 제공하는 장점을 갖지만, 많은 데이터 량으로 인해 실시간 처리가 어려운 문제점 또한 포함하고 있다. 또한 CCTV는 지능형 CCTV로의 기술적인 진보를 거듭하고 있으며, 대표적인 solution으로 증강현실(AR:Augmented Reality)을 꼽을 수 있다. 본 논문에서는 HD-CCTV의 최대 장점이라고 할 수 있는 실시간 영상에 선박의 정보(AIS : Automatic Identification System)을 결합하여 실시간으로 항만을 모니터링 하는 시스템을 구현하였다. 또한 750mm Zoom Lens를 탑재한 PanTilt 장비를 이용하여 선박을 targeting 하는 시스템 또한 구현하였다. 증강현실을 이용하여 실시간 영상과 선박 정보를 결합하였으며, 이를 구현하기 위해 perspective projection 방법을 통해 3차원 공간좌표계를 2차원으로 투영하였다. 실시간 처리를 위해 입력영상을 Block으로 분할하여 목적 좌표를 검색하였으며, 선박정보의 부드러운 이동을 위해 Dead Reckon 기법과 linear prediction 방법을 이용하여 선박 위치를 예측하였다. 마지막으로 삼각측량법에 기반하여 현재 PanTilt 장비를 목적된 장소로 이동시키는 시스템을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.727-730
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• 2004

영상은 복잡한 객체들의 집합으로 이루어져 있기 때문에 영상에 포함된 객체를 분리하는 일은 컴퓨터 비전이나 인식 등 많은 분야에서 중요시 된다. 영상 처리 측면에서 객체를 분할하기 위해서 색상, 모양, 질감, 움직임 등 다양한 기법들이 이용되고 있다. 본 논문에서는 정확한 색상의 비교를 위해서 CIE 색상 모델을 이용하고 있으며 이것을 기반으로 객체를 추출하고 있다. 그리고 추출된 객체의 해석과 검증을 위해서 모양 기반의 분석법을 이용하고 있다. 본 논문에서는 Pan/Tilt 카메라의 타겟팅(Targeting)과 포커싱(Focusing)을 위해 영상 내에 포함되어진 객체를 검출하기 위한 방법론을 제안하고자 한다. 객체를 인식하기 위해 CIE 색상 모델을 이용한 색상 매칭 기법을 제안하고 있다. 색상의 분포를 파악하기 위해서 CIE 모델이 생성해내는 Lab 블록을 통계적인 방법으로 분석한다. 그리고 분석된 결과는 CIE 블록 매칭(Bock Matching) 기법의 기준이 되며 이것을 이용해서 후보 객체 영역(Candidate Object Area)을 추출하게 된다. 추출된 후보 객체 영역을 검증하기 위해서 모멘트를 이용한 모양 기반의 분석을 활용하고 있다.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.195-204
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• 2024

In this paper, we investigate the comparative performance of two leading object detection architectures, YOLOv7 and Detection Transformer (DETR), across varying levels of data augmentation using CycleGAN. Our experiments focus on chest scan images within the context of biomedical informatics, specifically targeting the detection of abnormalities. The study reveals that YOLOv7 consistently outperforms DETR across all levels of augmented data, maintaining better performance even with 75% augmented data. Additionally, YOLOv7 demonstrates significantly faster convergence, requiring approximately 30 epochs compared to DETR's 300 epochs. These findings underscore the superiority of YOLOv7 for object detection tasks, especially in scenarios with limited data and when rapid convergence is essential. Our results provide valuable insights for researchers and practitioners in the field of computer vision, highlighting the effectiveness of YOLOv7 and the importance of data augmentation in improving model performance and efficiency.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.893-903
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• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.17-26
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• 2016

In the domestic game development field, game system planning is the work that game designers design the gameplay mechanics system to satisfy the game concepts in the perspective of creative design by data structural methods. But the programmers work to design the game system based on the results of the game system planning in the perspective of engineering design by object-oriented methods. This work process is a high risky way for high occurring probability of communication errors between the game designers and programmers, and mismatching errors in their work results. In this study, we propose an object-oriented design method of game system for the game designers in order to resolve this problem. The proposed method is a customized one of GRAPPLE object-oriented SW development guidelines to suit the game system planning. To investigate the effectiveness of the proposed planning method for the game designers, we carried out a survey targeting 10 game system designers working in the domestic game industry. The survey results show that the necessity and effectiveness of the proposed method is "a little over" for almost the game designers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.150-153
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• 2022

This paper reports a technique that automatically extracts object shapes through Dense-Net, and subsequently, detects the objects using Mask R-CNN in a manufacturing site, in which workers and objects are mixed. It is based on the customized factory dataset by targeting workers, machines, tools, control boxes, and products as the objects. Mask R-CNN supports multi-object recognition as a well-known object recognition method, while Dense-Net effectively extracts a feature from multiple and overlapping objects. After immediate implementation using the two technologies, the object is naturally extracted from a still image of the manufacturing site to describe image. Afterwards, the result is planned to be used to detect workers' abnormal behavior by adding a label on the objects.

• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.87-100
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• 2015

Currently, Korea government has strongly recommended the storm and flood insurance system to reduce the damage caused by natural disasters. The storm and flood insurance operated by private insurance company is the type of policy insurance. and is supervised by Minister of Public Safety and Security. It is the advanced disaster management system which is able to protect the public interests through unexpected natural disaster by assisting some part of the insurance premium from a central or local government. The main purpose of the present investigation is to build the insurance object GIS DB which should be necessary to calculate the premium rate in the map for storm and flood insurance, and also, to perform GIS analysis. The service model in this study is aimed to general single house, apartment and green house. The service management plan targeting the whole country has been investigated in terms of building DB and service operation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.861-870
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• 2014

According to the intelligence of the malicious code to extract the executable file in physical memory is emerging as an import researh issue. In previous physical memory studies on executable file extraction which is targeting running files, they are not extracted as same as original file saved in disc. Therefore, we need a method that can extract files as same as original one saved in disc and also can analyze file-information loaded in physical memory. In this paper, we provide a method that executable file extraction by analyzing information of Windows kernel file object. Also we analyze the characteristic of physical memory loaded file data from the experiment and we demonstrate superiority because the suggested method can effectively extract more of original file data than the existing method.