• Journal of Advanced Marine Engineering and Technology
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• v.29 no.2
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• pp.209-216
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• 2005

Thermo-chromic Liquid Crystal(TLC) particles were used as temperature sensor for thermal fluid flow. 1K $\times$ 1K CCD color camera and Xenon Lamp(500w) were used for the visualization of a Hele-Shaw cell The characteristic between the reflected colors from the TLC and their corresponding temperature shows strong non-linearity A neural network known as having strong mapping capability for non-linearity is adopted to quantify the temperature field using the image of the flow. Improvements of color-to-temperature mapping was attained by using the local color luminance (Y) and hue (H) information as the inputs for the constructed neural network.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.450-460
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• 2005

Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.277-279
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• 2013

본 논문에서는 광학적 방법을 이용하여 정색반응을 정량적으로 측정할 수 있는 방법을 제시한다. 정색반응은 발색, 변색의 현상을 일으키는 화학 변화로 시료 용액에 시약을 더하여 특수한 빛을 나타내게 하여, 물질을 정성적으로 검출하는데 이용된다. 하지만 정색반응 결과로 나타난 색상은 사람마다 색구별이 다르므로 정확한 양을 알 수는 없다. 본 연구에서는 시료의 양에 따라 색상 변화의 미세한 차이를 PICkit Serial Analyzer를 사용하여 색상을 수치화하여 시료의 양에 따른 색의 변화를 정량적으로 측정하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.165-173
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• 2015

People with color vision deficiency (CVD) experience difficulties in discriminating some color combinations and color differences due to the abnormal retinal cone systems. While there exist smartphones with a re-coloring function for CVD, monitors do not provide the re-coloring function. In this paper, we propose a new re-coloring algorithm that adjusts the displayed colors for CVD using a color controller embedded in the monitor. The proposed algorithm converts the hue and saturation in HSV color space, according to the type and strength of the color deficiency. The results of the performance evaluation with a certain number of people with CVD show that the proposed system can convert colors imperceptible into perceptible.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1213-1218
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• 2007

In this study, we have been constructed measuring system for spill over by the Japan TV broadcasting signals and analyzed those signals using APD curve. In Busan, we have been measured channel of Japan TV broadcasting signals during 9 months. The quality of image is that maximum grade is 2.5 level, and the quality of sound is that maximum grade is 3 level. In the result of analysis for measured Japan TV broadcasting signals, we have been observed Japan TV broadcasting signals those we have been chosen the ch 36 and ch 38, plotted the APD curve of each channel for a season, in Specially.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.237-245
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• 2017

This paper presents a fire detection algorithm using color and motion models from video sequences. The proposed method detects change in color and motion of overall regions for detecting fire, and thus, it can be implemented in both fixed and pan/tilt/zoom (PTZ) cameras. The proposed algorithm consists of three parts. The first part exploits color models of flames and smoke. The candidate regions in the video frames are extracted with the hue-saturation-value (HSV) color model. The second part models the motion information of flames and smoke. Optical flow in the fire candidate region is estimated, and the spatial-temporal distribution of optical flow vectors is analyzed. The final part accumulates the probability of fire in successive video frames, which reduces false-positive errors when fire-like color objects appear. Experimental results from 100 fire videos are shown, where various types of smoke and flames appear in indoor and outdoor environments. According to the experiments and the comparison, the proposed fire detection algorithm works well in various situations, and outperforms the conventional algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.236-238
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• 2003

Human face detection is often the first step in applications such as video surveillance, human computer interface, fare recognition, and image database management. We have constructed a simple and fast system to detect frontal human faces in complex environment and different illumination. This paper presents a fast segmentation method to combine neighboring pixels with similar hue. The algorithm constructs eye, mouth, and boundary maps for verifying each fare candidate. We test the system on images in complex environment and with confusing objects. The experiment shows a robust detection result with few false detected fates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11A
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• pp.1027-1037
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• 2010

In this paper, we propose the linear interpolation-based BD (Block Diagonalization) precoding approximation algorithm for low complexity in downlink multiuser MIMO-OFDM (Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing) systems. In the case of applying the general BD precoding algorithm to multiuser MIMO-OFDM systems, the computational complexity increases in proportional to the number of subcarriers. The proposed interpolation-based BD precoding approximation algorithm can be achieved similar SER performance with general BD algorithm and can decrease the computational complexity. It is proved that proposed algorithm can achieve the significantly decreased computational complexity by computer simulation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.55-60
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• 2014

In this paper, we proposed a method for face region extraction by skin-color hue, saturation and facial feature extraction in natural images. The proposed algorithm is composed of lighting correction and face detection process. In the lighting correction step, performing correction function for a lighting change. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. Eye detection using C element in the CMY color model and mouth detection using Q element in the YIQ color model for extracted candidate areas. Face area detected based on human face knowledge for extracted candidate areas. When an experiment was conducted with 10 natural images of face as input images, the method showed a face detection rate of 100%.