Earticle

본 논문은 이미지 처리 기술을 이용한 광 카메라 통신(OCC: Optical Camera Communications) 기술을 제안한다. OCC 시스템의구조 및 동작을 제안한다. 상용 30fps 카메라의 샘플링 동작에 의해 제한되는 데이터율을 증가시키기 위해 칼라 이미지 처리기술을이용한 멀티칼러 전송기법을 제안한다. 멀티칼라 부호화 및 이미지 처리기반의 복호화 기법을 제안한다.

This paper introduces the Optical Camera Communications (OCC) using image processing technique.The architecture andoperation of OCC system are given. To enhance data rate which is limited by sampling operation of commercial 30fpscamera, multi colors transmission technique is employed, leading to the importance of color image processing technique. Multi color encoding and image processing based decoding will be proposed in the paper.

Color image processing is very useful because color is a strong marker that also simplifies the recognition and extraction of objects from a scene and humans can distinguish thousands of shades of color and intensity compared to just around two dozen shades of grey. The processing of color images can be classified into two main areas as full-color and pseudo-colour. The images are first acquired with a full color sensor such as color TV camera, color scanner and second category has the question of assigning a color to a different monochrome intensity and intensity ranges. The aim of a color model is to promote color specification in a widely agreed way to some standard. A color model is a coordinate system specification and a subspace within that system where a single point represents each color. Some particular conversions can convert different color models to one another. This paper specify overview of different types of images, color models, their conversion and applications.

In recent year, many imaging systems have been developed, and it became increasingly important to exchange image data through the computer network. Therefore, it is required to reproduce color image independently on each imaging device. However, even if the image are same, perceived color is not always same under different viewing conditions. On the other hand, even if the image are different, we want to perceive same color under different viewing conditions. Therefore we must know the spectral reflectance information of object. We measured many reflectance human skin can be estimate using only three principal component. For Munsell color patches, five principle components were necessary to estimate the reflectance spectra. For that purpose, we have developed color image acquisition system that is composed of five band filters and CCD camera. Improved spectral reflectance of object is predicted by five band images taken by color image acquisition system and then we take account of camera's noise and component of object image for predicting accurate spectral reflectance of object. In the results, we confirmed that color difference and MSE(Mean Square Error) between measured and predicted spectral reflectance of object decreased into 0.0071 and 7.72 respectively.

we describes a method for realizing the color conversion from the tristimulus (X, Y, Z) values to the print ink signals (C, M, Y) by using neural networks. The realized nonlinear color conversion system consists of two hidden layers those have seventeen nodes. We determined the C, M, Y values of the input control signals to compensate the printer nonlinearity of real systems. Experimental results showed that the described method is useful and valid to realized the nonlinear color conversion.

This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

Quality sorting of cut flowers is very essential to increase the value of products. There are many factors that determine the quality of cut flowers such as length, thickness, and straightness of stem, and color and maturity of bud. Among these factors, the straightness of stem and the maturity of bud are generally considered to be more difficult to evaluate. A prototype grading and sorting machine for cut flowers was developed and tested for a rose variety. The machine consisted of a chain-drive feed mechanism, a pneumatic discharge system, and a grading system utilizing color image processing and neural network. Artificial neural network algorithm was utilized to grade cut roses based on the straightness of stem and maturity of bud. Test results showed 89% agreement with human expert for the straightness of stem and 90% agreement for the maturity of bud. Average processing time for evaluating straightness of the stem and maturity of the bud were 1.01 and 0.44 second, respectively. Application of neural network eliminated difficulties in determining criteria of each grade category while maintaining similar level of classification error.

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)

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)

Adjustable reflective color gamut RGBW transflective liquid crystal display (ARC RGBW TRLCD) applied simple manufacture process and image processing algorithm to achieve high brightness and good color performance both in transmissive and reflective mode. With appropriate modification higher transmittance but no color distortion happens in transmissive mode. Moreover, base on superior reflectance total brightness and color gamut also can be modified under different ambience. It provides the flexibility not only for any environments but also for variant personal hobbies. It is the best technique used both at indoor and outdoor.

The purpose of this study is to analyze the recent trend color of bathroom based on analysis result of digital color image processing, to analyze the emotional color of that, and to suggest the harmony color combination for the bathroom. It leads to the two final results. That is, the main color of bathroom image is recognized as three color classifications such as YR-Y, Y-GY, PB-P, 2) from the point of emotional aspect, the trend color of the bathroom can be classified into four image categories: 'modern', 'mild', 'elegant', 'natural'. Finally, under these categories, this paper propose 12 color harmony schema which can be applied to color in, especially bathroom Interior design.

The purpose of this study is to analyze the emotional color of home office and the trendy color with special comparison of office and library colors, and to suggest the harmony of color combination of home office based on the emotional color of this analytical data. this study, the Color Syntax Program, digital tool for color analysis of images is used. The results of this study are as follows. Firstly, the main color of home office images shows three color classifications of YR-Y, Y-GY, R-YR, and with relatively high ratios of YR-Y in the color of home offices, and B-PB, GY-G in offices and libraries. Secondly, from the point of emotional aspect, the trendy color of the home office can be classified into four color image categories: 'natural', 'peaceful', 'mild', and 'noble'. Under those categories this paper proposes 10 color harmony scheme that can be applied to color of home office interior design.

본 논문에서는 개선된 mean shift를 이용한 컬러 영상 분할을 소개한다. Mean shift는 Yizong Cheng에 의해 재조명되고 Dorin Comaniciu 등에 의해 정리되어 영상 필터링(image filtering), 영상 분할(image segmentation), 물체 추적(object tracking) 등 여러 응용 분야에 널리 활용되고 있다. 커널을 이용해 밀도를 추정하고 밀도가 가장 높은 점으로 커널을 연속적으로 이동함으로써 지역적으로 주요한 위치로 데이터 값을 갱신시킨다. 그러나 영상에 포함된 모든 화소에 대해 mean shift를 수행해야하기 때문에 연산 시간이 많이 소요되는 단점이 있다. 본 논문에서는 mean shift 필터링 과정을 분석하고 참조수렴방법과 강제수렴방법을 이용해 소요 시간을 단축시켰다. 모든 점에 대해 mean shift를 수행하는 대신 특정 조건을 만족하는 픽셀은 이웃 픽셀의 수렴 값을 참조하고, mean shift 과정에 진동 또는 미미한 이동을 계속하는 픽셀은 강제 수렴을 실시하였다. 개선된 방법과 기존의 mean shift 방식을 적용하여 영상 필터링과 영상 분할에 적용한 실험에서 결과 영상에는 차이가 적고 기존의 방법에 비해 수행 시간이 24% 정도 소요됨을 확인하였다.

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.

In general, the quality of agricultural products is determined by direct measurement of a weight or a magnitude, and it is determined by indirect or non-destructive method. In this paper, using color image processing, the algorithm to determine its quality and grading is presented. And the algorithm is applied to real-time citrus classifier. In the system, the size and color of orange are measured by not the sight of human but the digital image processing. The citrus classification system has the real-time maximum classification capacity of six quantify per one second. The system can be applied to controller design for the quality classification of agricultural products.

The quality of agricultural products is represented a degree of freshness and a special quality related to a commercial value. To grade cucumber, the charge-coupled device(CCD) camera is only used to measure external qualities like color. size and degree of bended cucumber The processed area of the image replaces the weigh of cucumber. That means there is no longer used the weighing beams. The system consists of Image processing system and distributing system. This paper explains the structure and movement of the automatic grade system and applies the algorithm for deformed cucumber and characteristics of cucumber through image processing to the grade system.

The quality of agricultural products is represented a degree of freshness and a special qualify that has a close relation to commercial value. To grade tomatoes, it used to nondestructive equipment of a charge-coupled device(CCD) camera and near-infrared(NIR) spectrum analysis method. The NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. The CCD camera is used to measure external qualities like color and a size of tomatoes. This paper explaines the structure and movement of the automatic grade system and applies the algorithm for deformed tomtatoes and characteristics of tomatoes through image processing to the grade system.

대상물체와 배경으로 이루어진 다변수 신호를 분리시키기 위한 변환 기법의 하나로 두 샘플 공분산 행렬의 정규화 후 동시 대각화를 이용한 변형된 Karhunen-Loeve 변환 기법이 제안되었다. 두 클래스간의 샘플 공분산비를 최대화함으로써 국소적 데이터 구조를 분리하는 이 변환 기법은 수리형태학적 연산자를 비롯한 인접 화소 연산자를 사용하는 다변수 영상처리 알고리듬의 전처리 변환으로 유망한 기법이라는 것을 보였다. 제안된 기법이 가지는 분리성은 수리형태학적 패턴 스펙트럼에 근거하여 제안된 measure인 ‘평균높이’의 개념과 관련시켜 해석하였다. 그리고 변환 기법에 대한 실용적인 구현 알고리듬과 이론적인 결과를 모의실험을 통하여 확인하였다.

A modified Karhunen-Loeve transformation technique using normalization and simultaneous diagonalization of two sample covariance matrices is proposed to separate the object from the background. The transformation technique for the separation of local data structure through maximizing the ratio of sample variances between two classes was identified as a promising one for a preprocessing of multi-variate signal processing algorithms using neighborhood operators including morphological filtering. To relate the separation quality of the proposed technique to a morphological measure, average height was defined by using morphological pattern spectrum. A practical implementation of the transformation technique was tested experimentally and the theoretical results were confirmed.

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.

Soil color is used to determine soil classification and its physical, chemical, and biological properties. Visual determination is the most commonly used method for identifying soil color. However, it is subjective and, in many cases, non-repeatable. Digital image processing obtains useful information from digital images, accelerates soil classification, and enables the rapid identification of soil types in a field. This study develops a digital image processing-based soil color analysis technology that can consider irregular light conditions in the field. The digital image studio was designed to simulate the characteristics of natural light (illuminance and color temperature). Also, digital images of two soil samples (Jumoonjin sand and Anseong weathered soil) were captured under 12 different light conditions. For the RGB and CIELAB color systems, soil color intensities of 24 images were obtained using digital image processing. CIELAB was suitable for dealing with irregular light conditions in the field.

최근 지질공학의 다양한 분야에 영상처리기법들이 적용되고 있다. 그러나 영상의 획득 및 분석 단계에서 발생하는 각종 오차에 관한 문제는 많은 부분 무시되어 왔다. 이에 본 연구에서는 암석영상처리의 신뢰도 향상을 위한 컬러보정기법을 개발하였다. 표준 컬러차트를 이용하여 컬러보정과 오차분석을 수행하였으며, 그 결과 영상처리의 신뢰도 향상과 영상들간의 상호 비교·분석을 꾀할 수 있었다.