• 한국지반공학회논문집
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• 제38권5호
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• pp.61-71
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• 2022

토색은 흙을 분류하고 물리적, 화학적, 생물학적 특성을 예측하기 위한 기초 지표로 널리 활용된다. 일반적으로 토색은 육안으로 관찰해 결정하지만 관찰자의 예민도 혹은 주관이 개입될 가능성이 높으며 많은 시간이 소요된다. 디지털 이미지 프로세싱은 디지털 이미지를 이용해 원하는 정보를 획득하는 일련의 과정으로, 이를 통해 빠르고 정확한(수치적인 혹은 통계적인) 토색 분석이 가능할 것으로 기대된다. 본 연구는 현장의 불규칙한 광조건을 고려할 수 있는 디지털 이미지 프로세싱 기반 토색 분석 기술 개발을 위한 기초단계로서 수행되었다. 자연광의 특성(조도 및 색온도)을 모사할 수 있는 디지털 이미지 촬영 스튜디오를 구축하고, 두 가지 흙 시료(주문진 표준사 및 안성 풍화토)를 대상으로 광조건을 12회 씩 바꿔가며 디지털 이미지를 촬영했다. 디지털 이미지 프로세싱을 통해 촬영된 시료의 토색을 두 가지 색 표시계(RGB, CIELAB)에 대해 추출한 결과, CIELAB 색 표시계를 활용해 현장의 불규칙한 광조건을 고려할 수 있음을 확인했다.

• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1741-1749
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• 2017

In commercial digital-cameras, color-filter filters light according to wavelength range of color filter array (CFA) and the filtered intensities contain color information of light. Then, output data of CFA is transformed to final rendered image through demosaicing process. In image processing of digital-camera, the quality of the final rendered image is affected by optical cross talk of CFA, kind of CFA pattern etc. Basically, pattern of CFA plays important role in image quality of final image rendered by digital-camera. Therefore, an evaluation system capable of quantitatively evaluating CFA is needed. This paper proposes a novel evaluation system using existing and proposed image metrics for evaluating CFAs of digital-camera. Proposed CFA evaluation system consist of color difference in CIELAB and S-CIELAB, Structure SImilarity (SSIM), MTF50, moire starting point (MSP), and subjective preference (SP). MSP and SP are newly designed for the proposed evaluation system. Proposed evaluation system is expressed in polar coordinates to analyze the characteristics of CFA objectively and intuitively. Through simulations, we confirmed that proposed CFA evaluation system can objectively assess performance of developed CFAs.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2000년도 추계학술발표논문집 (하)
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• pp.871-874
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• 2000

디지털 카메라(Digital Camera)와 같은 휴대형 영상 입력 장치(Portable Image Input Device)는 스캐너 (Scanner)와 달리 3 차원의 피사체(Object)를 디지털 영상으로 생성할 수 있고 다양한 조명 환경(Illuminant)에서 사용할 수 있다는 이유로 많은 응용 분야에서 활발하게 사용되고 있다. 그러나, 정확한 색 재현(Color Reproduction)을 위한 기존의 디지털 카메라 특성화 방법(Digital Camera Characterization Method)은 생성된 영상의 조명 정보를 고려하지 않은 상태에서 색 변환 행렬을 생성하므로 다양한 조명 환경 변화에 대해 적응적으로 대처하지 못하는 단점이 있다. 본 논문에서는 디지털 카메라가 생성하는 영상의 rgb 색도를 이용하여 색도 평면에 색도 다각형(Chromaticity Polygon)을 구성하고 각 색도 다각형들간의 포함 관계에 따라 조명 정보를 평가함으로써 조명색(Illuminant Color)의 변화에 따른 인간 시각 시스템(Human Visual System)의 색 불변성(Color Constancy)을 재현할 수 있는 디지털 카메라 특성화 방법을 제안한다.

• 한국컴퓨터정보학회논문지
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• 제22권6호
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• pp.131-140
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• 2017

As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

• 감성과학
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• 제5권3호
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• 대한음성언어의학회:학술대회논문집
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• 대한음성언어의학회 1998년도 제10회 학술대회 심포지움
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• pp.192-193
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• 1998

Introduction : Laryngeal lesions were observed using the OLYMPUS EVIS-200 electronic videoendoscope system attached to the OLYMPUS ENF-200 rhinolarynx endoscope portion. This endoscope portion can be introduced into the laryngeal cavity by inserting it through the nasal passages. Since it is also possible to connect the OLYMPUS EVIP-230 digital image processor capable of processing dynamic images in real time to this system, an attempt has also been made to process the dynamic color images of laryngeal lesions obtained with the electronic videoendoscope system. Structure enhancement and color enhancement were peformed as processing images. The images of laryngeal lesions obtained with this system and the processed images are presented and described from the standpoint of diagnostic usefulness (omitted)

• 한국산업정보학회논문지
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• 제5권3호
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• pp.65-70
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• 2000

일반적으로 농산물의 품질은 무게나 크기 등을 직접 측정하여 판정하거나 간접 또는 비파괴방법을 이용하여 판정하게 된다. 본 논문에서는 비파괴를 이용한 판정방법인 칼라 영상처리를 이용하여 농산물의 품질과 등급을 결정하는 알고리즘을 개발하여, 이를 실시간 귤 분류시스템에 적용하였다. 개발된 시스템은 귤의 크기와 색상을 칼라 영상처리 하여 초당 최대 6개를 실시간 분류 할 수 있는 성능을 가지고 있다. 또한 다른 농산물의 품질판정을 위한 제어기를 설계할 경우에도 본 논문에서 개발한 알고리즘이 적용될 수 있을 것으로 기대된다.

• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.8-16
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• 2012

An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.99-106
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• 2019

In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

• Smart Structures and Systems
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• 제17권6호
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.