• 품질경영학회지
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• 제44권3호
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• pp.527-540
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• 2016

Purpose: The purpose of this study was to propose contrast metric which is based on the human visual perception and thus it can be used to improve the quality of digital images in many applications. Methods: Previous literatures are surveyed, and then the proposed method is modeled based on Human Visual System(HVS) such as multiscale property of the contrast sensitivity function (CSF), contrast constancy property (suprathreshold), color channel property. Furthermore, experiments using digital images are shown to prove the effectiveness of the method. Results: The results of this study are as follows; regarding the proposed contrast measure of complex images, it was found by experiments that HVS follows relatively well compared to the previous contrast measurement. Conclusion: This study shows the effectiveness on how to measure the contrast of complex images which follows human perception better than other methods.

• 전기전자학회논문지
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• 제17권4호
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• pp.398-406
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• 2013

핵의학 영상 기기인 양전자 방출 단층 촬영 장치(Positron emission tomography: PET)와 같은 진단기기는 방사성의약품을 인체에 주입하여 질병을 진단한다. 이 때 사용되는 방사성의약품은 안전성을 위하여 적절한 수소 이온농도를 가져야 한다. 일반적으로 방사성 의약품의 수소 이온 농도를 측정하는 과정에서 흔히 사용되는 것이 pH시험지이다. 표본을 pH 시험지에 떨어뜨려 pH 시험지의 변색 정도를 표준색상표(Standard color chart)와 비교하여 표본의 pH를 알 수 있다. 그러나 이 방법은 측정자의 경험 정도에 따라 pH 측정값에 차이가 발생할 수 있다. 또한 pH 메타기는 고감도의 센서를 사용함으로 오염에 주의해야 한다. 이러한 불편함을 고려하여 쉽고 간단하게 정확한 pH를 측정하기 위한 새로운 장치 제작과 영상 기반 알고리즘을 통한 소프트웨어를 개발하였다. 이렇게 개발한 장치는 최종적으로 방사성의약품의 생산 시 품질관리(QC) 통합 제어 시스템으로 사용된다.

• 반도체디스플레이기술학회지
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• 제16권4호
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• pp.97-102
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• 2017

Object detection and tracking have become one of the most active research areas in the past few years, and play an important role in computer vision applications over our daily life. Many tracking techniques are proposed, and Camshift is an effective algorithm for real time dynamic object tracking, which uses only color features, so that the algorithm is sensitive to illumination and some other environmental elements. This paper presents and implements an effective moving object detection and tracking to reduce the influence of illumination interference, which improve the performance of tracking under similar color background. The implemented prototype system recognizes object using invariant features, and reduces the dimension of feature descriptor to rectify the problems. The experimental result shows that that the system is superior to the existing methods in processing time, and maintains better problem ratios in various environments.

• 대한원격탐사학회지
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• 제4권1호
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• pp.31-40
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• 1988

Low-cost microcomputer systems can be assembled which possess computing power, color display, memory, and storage capacity approximately equal to graphic workstactions. A low-cost, flexible, and user-friendly IBM/PC/XT/AT based image processing system has been developed and named as KMIPS(KAIST (Korea Advanced Institute of Science & Technology) Map and Image Processing Station). It can be easily utilized by the resource managers who are not computer specialists. This system can: * directly access Landsat MSS and TM, SPOT, NOAA AVHRR, MOS-1 satellite imagery and other imagery from different sources via magnetic tape drive connected with IBM/PC; * extract image up to 1024 line by 1024 column and display it up to 480 line by 672 column with 512 colors simultaneously available; * digitize photographs using a frame grabber subsystem(512 by 512 picture elements); * perform a variety of image analyses, GIS and terrain analyses, and display functions; and * generate map and hard copies to the various scales. All raster data input to the microcomputer system is geographically referenced to the topographic map series in any rater cell size selected by the user. This map oriented, georeferenced approach of this system enables user to create a very accurately registered(.+-.1 picture element), multivariable, multitemporal data sets which can be subsequently subsequently subjected to various analyses and display functions.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.746-750
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• 2005

This paper describes image processing techniques that can detect, segment, and analyze the mango's physical properties such as size, shape, surface area, and color from images. First, images of mangoes taken by a digital camera are analyzed and segmented. The segmentation is done based on constructed hue model of the sample mangoes. Some morphological and filtering techniques are then applied to clean noises before fitting spline curve on the mango boundary. From the clean segmented image, the mango projected area can be computed. The shape of the mango is then analyzed using some structuring models. Color is also spatially analyzed and indexed in the database for future classification. To obtain the surface area, the mango is peeled. The scanned image of its peels is then segmented and filtered using similar approach. With calibration parameters, the surface area could then be computed. We employed the system to evaluate physical properties of a mango cultivar called "Nam Dokmai". There were sixty mango samples in three various sizes graded by an experienced farmer's eyes and hands. The results show the techniques could be a good alternative and more feasible method for grading mango comparing to human's manual grading.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1243-1253
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• 1993

Visual features of a mushroom(Lentinus Edodes L) are critical in sorting and grading as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. Though actions involved in human grading looks simple, a decision making undereath the simple action comes form the results of the complex neural processing of the visual image. And processing details involved in the visual recognition of the human brain has not been fully investigated yet. Recently, however, an artificial neural network has drawn a great attention because of its functional capability as a partial substitute of the human brain. Since most agricultural products are not uniquely defined in its physical properties and do not have a well defined job structure, a research of the neuro-net based human like information processing toward the agricultural product and processing are widely open and promising. In this pape , neuro-net based grading and sorting system was developed for a mushroom . A computer vision system was utilized for extracting and quantifying the qualitative visual features of sampled mushrooms. The extracted visual features and their corresponding grades were used as input/output pairs for training the neural network and the trained results of the network were presented . The computer vision system used is composed of the IBM PC compatible 386DX, ITEX PFG frame grabber, B/W CCD camera , VGA color graphic monitor , and image output RGB monitor.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.319-320
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• 2006

In this paper, we propose a vision based system employing two cameras to provide effective touch screen function. The two main processes - determining touch (or no-touch) and contact location of screen plane - are essential for enabling touch screen function. First region of interest is found by using color characteristic and histogram for determining the contact mode. Second, if the hand touches the mirror, the fingertip point in image is found using the correlation coefficient based on the mirror attribute. Subsequently, the fingertip coordinate in image is transformed to the location in mirror plane by using four predefined points (termed as four-point method) and bilinear transform. Representative experimental results show that the proposed system is suited to touch screen.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• 한국정보통신학회논문지
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• 제14권2호
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• pp.462-468
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• 2010

본 논문에서는 기존의 full color LED 전광판 영상 처리 방식을 개선시킨 획기적인 영상 구동 처리 기술을 제안하였다. 이 기술은 고화질의 대형 TV나 LCD Display에 적용 가능하며 선명한 표출구동의 영상제어를 가능하게 한다. 제안한 구동 제어 방식은 기존의 영상처리 기능을 효율적으로 보강할 수 있다. 자동 또는 수동으로 contrast, bright, tint, color, 감마보정 등의 영상 변화처리 조절이 가능하므로 선명한 화질을 얻을 수 있다. 그리고 경제적인 가격으로 구현이 가능하다.

• 한국항행학회논문지
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• 제21권3호
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• pp.251-257
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• 2017

차량의 정확한 위치 추정을 위하여 GPS (global positioning system)와 영상 센서, 관성 센서 등을 결합한 복합 측위에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 복합 측위에 있어 중요한 요소 중 하나인 각 센서 간의 시각동기화 기법을 제안한다. 제안된 기법은 GPS 시각 정보를 기준으로 시각동기화 된 영상 센서, 관성 센서와 OBD (on-board diagnostics) 측정치를 획득하는 기법이다. GPS로부터 시각 정보와 위치 정보를 획득하며, 관성 센서로부터 차량의 자세에 관련된 측정치와 OBD를 활용하여 차량의 속력을 획득한다. 영상 센서로부터 획득한 영상에 GPS 시각 정보와 위치 정보, 관성 센서와 OBD의 측정치를 색상으로 변환하여 영상 픽셀에 삽입하는 기법을 제안한다. 또한, 영상에 삽입된 시각동기화 된 센서 측정치들은 변환 과정을 통하여 추출할 수 있다. 각 센서들의 결합을 위하여 임베디드 리눅스 보드를 활용하였으며, 제안된 기법의 성능 평가를 위하여 실제 차량 주행을 통한 실험을 수행하였다.