• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.133-140
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• 2020

This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.260-263
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted leastsquaresfiltering with iCAM06, for showing more perceptual high dynamic range images in conventional display, while avoiding visual halo artifacts. We decompose high dynamic range image into base layer and detail layer. The base layer has large scale variation, it is obtained by using weighted least squares filtering, and then the base layer incorporates iCAM06 model. Then, adaptive compression on the base layer according to human visual system. Only the base layer reduces contrast, and preserving detail. The resultshows more perceptual color appearance and preserve fine detail, while avoiding common artifacts.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.444-447
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• 2008

In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

• ETRI Journal
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• v.33 no.1
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• pp.78-88
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• 2011

In this paper, we present the Touch Text exTractor (Touch TT), an interactive text segmentation tool for the extraction of scene text from camera-based images. Touch TT provides a natural interface for a user to simply indicate the location of text regions with a simple touchline. Touch TT then automatically estimates the text color and roughly locates the text regions. By inferring text characteristics from the estimated text color and text region, Touch TT can extract text components. Touch TT can also handle partially drawn lines which cover only a small section of text area. The proposed system achieves reasonable accuracy for text extraction from moderately difficult examples from the ICDAR 2003 database and our own database.

• Textile Coloration and Finishing
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• v.20 no.5
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• pp.23-27
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• 2008

In this work, poly(diallyldimethylammoniumchloride) (PDDAC) and meso-tetrakis(4-carboxyphenyl)porphyrin were considered to produce the self-assembly fabrication films. This method is based on the layer-by-layer (LbL) deposition produced by the electrostatic attraction between positively charged PDDAC and negatively charged porphyrin ions. The result of multilayer fabrication was discussed with the level of color strength (K/S). K/S spectra of the fabricated multilayer films showed gradual increase behaviors. In addition, the color photo images of the fabricated multilayer films showed that PDDAC and porphyrin were successfully attracted by electrostatic self-assembly forces.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.222-226
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• 2007

We suggest the fluorescence endoscope system that has light source apparatus providing selectable white or excitation light. White light source generates normal color images and is easily switched over to excitation light with the wide spectrum range from 380 nm to 580 nm. 5-ALA is deposited selectively in the abnormal tissue like cancer and causes fluorescence in the red spectrum range when excited by blue spectrum range. In addition, the others of excitation light make the color background image by reflected light to allow accurate orientation and visualization of the abnormal tissue and around. According to clinical studies, the fluorescence intensity contrast that defines the fluorescence intensity of lesion over the fluorescence intensity of around has more than 2 in tumour. Proposed system is useful and objective way in early diagnosis. Furthermore, it can be used in the biopsy for tumour classification at the highest fluorescence intensity point.

• Proceedings of the KAIS Fall Conference
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• 2011.12b
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• pp.431-433
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• 2011

본 논문에서는 컬러 화재영상에 포함된 화염의 색상 분석과 시공간적 특징 분석을 통하여 신뢰성 높은 화재 판정 조건을 제시한다. 이를 위하여 컬러영상에서 화염을 판정하는 컬러속성으로서 Y-휘도 성분과 Cr-색차 성분을 조합한 문턱치를 도출하고 화염 후보영역을 선정하였다. 선정된 화염 후보영역에 대해서는 화염의 공간적인 질감분석과 시간적인 동적변화를 DCT와 프레임간 휘도성분 변화량을 분석하여 최종 화염 판정 기준으로 제시하였다. 컴퓨터 모의실험 결과, 제시한 화염 판정 조건의 신뢰성과 실용성을 확인하였다.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.