• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.213-217
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• 2004

The general method to find a H. pylori in the stomach is the rapid urease test but it is only used to decide the infection with H. pylori. In this study, it is tried to develope fiber-optic pH sensor which can be used with gastroscop to quantify H. pylori. To measure the degree of infection with H. pylori, the color change of phenol red according to the degree of pH is measured by optical fibers with different light sources and the optimum distance from a sample to the end of sensor tip is decided by measuring the maximum reflectivity from a sample. Also the sensitivity study is carried out to decide the optimum light source which has sensitive change of reflectivity to the change of pH. It is expected that the fiber-optic pH sensor which measures the degree of infection with H. pylori exactly can be developed.

• Journal of Sensor Science and Technology
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• v.20 no.4
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• pp.266-271
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• 2011

A reflection-type fiber-optic pH sensor, which is composed of a pH sol-gel film, plastic optical fibers, a mirror, a light source and a spectrometer, is developed in this study. As pH indicators, a bromthymol blue, a cresol red and a thymol blue are used, and they are immobilized in the sol-gel films. The emitted light from a light source is guided by a fiber-optic Y-coupler and plastic optical fibers to the pH sol-gel film in a pH sensing probe. The pH change in the sensing probe gives rise to a change in the color of the pH sol-gel film, and the optical characteristic of reflected light through the pH sol-gel film is also changed. Therefore, we have measured the spectra of reflected lights, which are changed according to the color variations of the pH sol-gel films with different pH values, by using of a spectrometer. Also, the relationships between the pH values and the intensities of reflected lights are obtained on the basis of the color variations of the pH sol-gel films.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1317-1324
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• 2016

Utilizing the Arduino platform to express the emotions that reflect the colors expressed the jewelry. Emotional color expression utilizes Plutchik's Wheel of Emotions model was applied to the similarity of emotions and colors. It receives the recognized value from the temperature, lighting, sound, pulse sensor and gyro sensor of a smart jewelery that can be easily accessible from your smartphone processes that recognize and process the emotion applied the rules of inference based on ontology. The emotional feelings color depending on the color looking for the emotion seen in context and applied to the smart LED jewelry. The emotion and the color combination of contextual information extracted from the recognition sensors are reflected in the built-in smart LED Jewelry depending on the emotions of the wearer. Take a light plus the emotion in a smart jewelery can represent the emotions of the situation, the doctor will be able to be a tool of representation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.175-186
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• 2018

Due to global warming, various natural disasters such as floods and localized heavy rains are increasing. If a natural disaster can be detected and analyzed in advance and effectively, it can prevent enormous damage due to natural disasters. Recent development in visual sensor technologies has encouraged various studies on monitoring environments including rivers. In this paper, we propose a method to detect river regions from river images which can be exploited for river surveillance systems using video sensor networks. In the proposed method, we first analyze the color properties of the river region and the background region of a image and then propose a way to select the proper color channel and binarize the image to detect the river region. It is shown by experimental results that the proposed method is simple but detects river regions accurately.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.933-940
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• 2022

In this paper, the algorithm was developed to recognize hand 3D position through 2D image sensor and implemented a system to remotely control the 6 d.o.f. robot arm by using it. The system consists of a camera that acquires hand position in 2D, a computer that controls robot arm that performs movement by hand position recognition. The image sensor recognizes the specific color of the glove putting on operator's hand and outputs the recognized range and position by including the color area of the glove as a shape of rectangle. We recognize the velocity vector of end effector and control the robot arm by the output data of the position and size of the detected rectangle. Through the several experiments using developed 6 axis robot, it was confirmed that the 6 d.o.f. robot arm remote control was successfully performed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.9-18
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• 2006

In the digital camera system, CMOS image sensor (CIS) is widely used because its size and weight become smaller and power consumption becomes lower. However, there are common problems that colors of the recorded image do not match those of the photographed object and that spectral sensitivity of the CIS used in different cameras varies largely in each case. Therefore, color correction is needed because the spectral sensitivity of the CIS in each color is neither the same color component for most standard colors nor the appropriate color representation for any output devices. In the conventional method, a color correction is empirically obtained by a large number of iterative experiments, but the result is not so satisfied. In this paper, a new method to obtain the efficient color correction matrix for digital camera using CIS is proposed. We obtain camera transfer matrix under the certain white-balance point, and color correction matrix that makes the transfer characteristic of digital camera close to the transfer characteristic of ideal camera is obtained. The experimental results show that the transfer characteristic of digital camera by the proposed method is close to that of the ideal camera. In addition, the image quality of pictures of digital camera using the proposed method is dramatically improved.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.86-97
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• 2011

This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1354-1363
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• 1993

Optical methods were developed to examine their feasibility for quality evaluation of peanut with pod. Surface color and internal quality of peanut were measured without contact. The surface color of peanut was measured by light reflectance at a region of visible wavelengths. Its characteristic was high correlated with a visual grading of peanut. A trial machine for the color grading of peanut was developed using an optical sensor and it was considered to compare with the visual grading. The spectral reflectance at a region of near infrared wavelengths from 1,200 to 2,500nm was measured , and the chemical components of peanut were related to spectral reflectance at special wavelengths. The protein, fat and moisture contents of peanut were estimated by the near infrared methods. An infrared imaging method was developed to evaluate the internal quality of peanut with pod. As thermal characteristic of peanut with pod was deeply related to internal quality , the quality of peanut can be evaluated by temperature changes on the surface of peanut. Measurement of surface color, near infrared reflectance and thermal imaging were shown to be very effective in grading of peanut with pod.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.137-144
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• 2017

Face detection is still a challenging task under severe face pose variations in complex background. This paper proposes an effective algorithm which can detect single or multiple faces based on skin color detection and depth information. We introduce Gaussian mixture model(GMM) for skin color detection in a color image. The depth information is from three dimensional depth sensor of Kinect V2 device, and is useful in segmenting a human body from the background. Then, a labeling process successfully removes non-face region using several features. Experimental results show that the proposed face detection algorithm can provide robust detection performance even under variable conditions and complex background.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.153-162
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• 2004

In the summer of 1998-2001, a huge flood occurred in the Yangtze River in the eastern China. Low salinity water less than 28 psu from the river was detected around the southwestern part of the Jeju Island, which is located in the southern part of the Korean Peninsula. We studied how to detect low salinity water from the Yangtze River, that cause a terrible damage to the Korean fisheries. We established a relationships between low salinity at surface, turbid water from the Yangtze River and digital ocean color remotely sensed data of SeaWiFS sensor in the northern East China Sea, in the summer of 1998, 1999, 2000 and 2001. The salinity charts of the northern East China Sea were created by regeneration of the satellite ocean color data using the empirical formula from the relationships between in situ low salinity, in situ measured turbid water with transparency and SeaWiFS ocean color data (normalized water leaving radiance of 490 nm/555 nm).