• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.117-125
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• 2011

In this paper, it was segmented the face color distribution using YCbCr color model, which is one of the feature-based methods, and preprocessing stage was to be insensitive to the sensitivity for light which is one of the disadvantages for the feature-based methods by the quantization. In addition, it has raised the accuracy of image synthesis with characteristics which is selected the object of the most same image as the shape of pattern using rough set. In this paper, the detection rates of the proposed face detection algorithm was confirmed to be better about 2~3% than the conventional algorithms regardless of the size and direction on the various faces by simulation.

• Journal of Digital Contents Society
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• v.6 no.3
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• pp.169-174
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• 2005

In this paper we propose efficient design and implementation of JPEG image display board that can display JPEG image on TV. we used NAND Flash Memory to save the compressed JPEG bit stream and video encoder to display the decoded JPEG mage on TV. Also we convert YCbCr to RGB to super impose character on JPEG image. The designed B/D is implemented using FPGA.

• Journal of the Korean Society of Radiology
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• v.5 no.6
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• pp.421-426
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• 2011

This research was accomplished to assess dose effects on image quality at computed radiography (CR). The ultimate target of the research was finding optimized exposure that provides necessary image quality for the clinical chest diagnosis. Modulation transfer function (MTF), normalized noise power spectrum (NNPS), and Noise equivalent quanta (NEQ) corresponding to the different doses were measured for the assessment of image quality. The preparation of "edge test device" used in MTF measurement and experimental geometry setup were followed by the recommendations of International Electrotechnical Commission (IEC). The experimental results show the necessary image quality can be achieved even at a half of the automatic exposure control (AEC) setting dose for chest diagnosis. It means that the patient exposure can be reduced dramatically by using optimized dose.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.50-60
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• 2000

In this paper, we propose a new composite feature consists of both color and shape information that are suitable for the task of character image retrieval. This approach extracts shape-based information using Zernike moments from Y image in YCbCr color space. Zernike moments can extract shape-based features that are invariant to rotation, translation, and scaling. We also extract color-based information from the DCT coefficients of Cr and Cb image. This approach is good method reflecting human visual property and is suitable for web application such as large image database system and animation because higher retrieval rate has been achieved using only 36 features. In experiment, this method is applied to 3,834 character images. We confirmed that this approach brought about excellent effect by ANMRR(Average of Normalized, Modified Retrieval Rank), which is used in the evaluation measure of MPEG-7 color descriptor and BEP(Bull's Eye Performance), which is used in evaluation measure of shape descriptor in character image retrieval.

• Journal of the Korean Solar Energy Society
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• v.26 no.1
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• pp.57-64
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• 2006

Cr-CrO cermet solar selective coatings with a double cermets layer film structure were prepared using a special direct current (dc) magnetron sputtering technology. The typical films structures from surface to bottom substrate were measured to be an $Al_2O_3$ anti-reflection layer on a double Cr-CrO cermet layer on an Al metal infrared reflection layer. Optical properties of optimized Cr-CrO cermet solar selective coating were absorptance (${\alpha}$) = 0.95 and emittance (${\varepsilon}$) = 0.10 ($100^{\circ}C$). Atomic force microscopy (AFM) image showed that Cr-CrO cermet film was very smooth and their grain size was also very small The results of thermal stability test showed that the Cr-CrO cermet solar selective coatings were stable for use at temperature of $400^{\circ}C$.

• Korean Journal of Digital Imaging in Medicine
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• v.5 no.1
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• pp.64-77
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• 2002

DR has had an important fact not only in the department of radiology but also in productivity or work efficiency of a whole hospital. The environment of DR has more various parameter than CR, so it is able to supply high quality of medical services. The current environment of radiology department in each hospital has been changed from Film-Screen system to DR through Full-PACS. This hospital which uses Full-PACS became to study the proper condition of CR and DDR and how the image quality of them is expressed among general photographing systems in the DR environment. From this experiment, the image quality of DDR is better than CR under the same exposure condition. And in the DDR system, the score of image which uses AEC is a little higher than the score which doesn't use it. Especially it can be known that the function of AEC of DDR is useful to improve the image quality in the part of skull and chest. (The function of AEC : It is the tool that detects the ionized current of x-ray which goes through objects with using the ion chamber which is in the detector. Also it controls the examination of X-ray when the proper density is reached.) Because the proper degree of density can be represented by this system, the photographing can be taken much easily without consideration of the exposure condition with the thickness of various objects. From the result of this experiment, it can be known that the selection of proper exposure condition plays an important rule to gain good Image Quality. More researches will be necessary about DDR system which has potential ability in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.717-724
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• 2016

This paper proposes a change detection method based on the covariance matrices of color and edge gradient in a color video. The YCbCr color format was used instead of RGB. The color covariance matrix was calculated from the CbCr-channels and the edge gradient covariance matrix was calculated from the Y-channels. The covariance matrices were effectively calculated at each pixel by calculating the sum, squared sum, and sum of two values' multiplication of a rectangle area using the integral images from a background image. The background image was updated by a running the average between the background image and a current frame. The change areas in a current frame image against the background were detected using the Mahalanobis distance, which is a measure of the statistical distance using covariance matrices. The experimental results of an expressway color video showed that the proposed approach can effectively detect change regions for color and edge gradients against the background.

• Journal of Radiation Protection and Research
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• v.38 no.1
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• pp.29-36
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• 2013

The aim of this study was to determine the correlation between exposure index (EI) and dose factors related to radiation dose optimization in digital radiography (DR) system. Two phantoms with built-in regional test object for quantitative assessment of images were used to produce image signals that acquired in chest radiography background. EI and entrane surface dose (ESD) increased proportionally with rise of radiation dose (kVp, mAs) in both DR and CR systems. Especially, DR detector was effective to form good contrast and hence, reached easily to improvement of image quality with minimal dose changes. It made operators possible to expect the accuracy of EI values deeply related to absorbed dose of the detector. The evaluation of images was obtained specially employed calculation of noise to signal ratio (NSR) and contrast to noise ratio (CNR). These measurements were performed for how exposure factors affect image quality. NSR was inversely proportional to kVp and mAs and low NSR represented high signal detection efficiency. Consequently, EI values was the measure of the amount of exposure received by the image receptor and it was proportional to exposure factors. Therefore the EI in a recommended range from manufacturer can offer optimal image quality. Also, continuous monitoring of EI values in the digital radiography can reduce the unnecessary patient dose and help the quality control of the system.

• Imaging Science in Dentistry
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• v.35 no.3
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• pp.157-165
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• 2005

Purpose : To find out the proper compression ratios without degrading image quality and affecting lesion detectability on diagnostic images used in dentistry compressed with JPEG 2000 algorithm. Materials and Methods : Sixty Digora periapical images, sixty panoramic computed radiographic (CR) images, sixty computed tomographic (CT) images, and sixty magnetic resonance (MR) images were compressed into JPEG 2000 with ratios of 10 levels from 5:1 to 50:1. To evaluate the lesion detectability, the images were graded with 5 levels (1 : definitely absent; 2: probably absent; 3: equivocal; 4: probably present; 5: definitely present), and then receiver operating characteristic analysis was performed using the original image as a gold standard. Also to evaluate subjectively the image quality, the images were graded with 5 levels (1 definitely unacceptable; 2: probably unacceptable; 3: equivocal, 4: probably acceptable; 5· definitely acceptable), and then paired t-test was performed. Results : In Digora, CR panoramic and CT images, compressed images up to ratios of 15 : 1 showed nearly the same lesion detectability as original images, and in MR images, compressed images did up to ratios of 25 : 1. In Digora and CR panoramic Images, compressed images up to ratios of 5 : 1 showed little difference between the original and reconstructed images in subjective assessment of image quality In CT images, compressed images did up to ratios of 10: 1 and in MR images up to ratios of 15 : 1 Conclusion : We considered compression ratios up to 5 : 1 in Digora and CR panoramic images, up to 10 : 1 in CT images, up to 15 : 1 in MR images as clinically applicable compression ratios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3172-3193
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• 2018

Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.