• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.527-530
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• 2003

In this paper, we implemented the voxel coloring method to reconstruct 3D object from synthetic input Images. Then compare the result between using standard voxel coloring and using coarse-to-fine method. We compared using different voxel space site to see the difference of time processing and the result of 3D object. Photorealistic 3D object reconstruction is a challenging problem in computer graphics. Vexel coloring considered the reconstruction problem as a color reconstruction problem, instead of shape reconstruction problem. This method works by discretizing scene space into yokels, then traversed and colored those in special order. Also there is an extension of voxel coloring method far decreasing the amount of processing time called coarse-to-fine method. This. method works using low resolution instead of high resolution as input and after processing finish, apply some kind of search strategy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.551-555
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• 2019

본 논문에서는 색채에 대한 아동의 심리를 분석하기 위해서 CRR(Colour Reflection Reading) 및 주조색를 이용한 심리 분석 기법을 제안한다. CRR은 이미 그려진 그림에 아동이 색을 칠하는 것으로 색이 칠해진 데이터를 바탕으로 아동의 심리 상태를 분석한다. 주조색 심리 분석 기법은 원하는 색을 선택하여 그림을 그리고, 그린 그림을 이용하여 심리를 분석한다. 따라서 본 논문에서는 퍼지 논리를 적용하여 색채에 대한 심리 분석 결과를 도출하고 그린 그림을 기반으로 공간 배치도 분석 기법을 이용하여 공간 배치도에 따른 아동의 심리 상태도 분석한다.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.385-391
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• 2021

3D modeling of the human body is an integral part of computer graphics. Among them, several studies have been conducted on hair modeling, but there are generally few studies that effectively implement hair and face modeling simultaneously. This study has the originality of providing users with customized face modeling and hair modeling that is different from previous studies. For realistic hair styling, We design and realize hair segmentation using FCN, and we select the most appropriate model through comparing PSPNet, DeepLab V3+, and MobileNet. In this study, we use the open dataset named Figaro1k. Through the analysis of iteration and epoch parameters, we reach the optimized values of them. In addition, we experiment external parameters about the location of the camera, the color of the lighting, and the presence or absence of accessories. And the environmental analysis factors of the avatar maker were set and solutions to problems derived during the analysis process were presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.357-360
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• 2011

스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 이러한 맥락에서 본 논문에서는 음원의 분위기와 분위기 단어의 색상을 수집한 후 수집한 데이터를 이용하여 음악 장르에 따른 분위기 분포와 분위기 단어에 따른 색상을 이용하여 음악 장르에 따른 색상 분포가 다르다는 것을 확인하기 위해 Minitab을 이용하여 $x^2$-test를 실시하였다. 분석결과, P<0.001로 음악 장르에 따라 분위기 색상이 다르게 분포되며 분위기에 따라 색상 및 명도, 채도의 분포도 다르게 나타남을 확인하였다.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.599-610
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• 2010

Color laser printers are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. Since different printer companies use their own printing process, each of printed papers from different printers has a little different invisible noise. After the wiener-filter is used to analyze the invisible noises from each printer, we extract some features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, we use total 2,597 images from 7 color laser printers. The results prove that the presented identification method performs well using the noise features of color printed images.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.986-995
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• 2009

Color affects people in their various combinations of hue, saturation and value. On the other hand, people may feel different emotion from the same color. If we can introduce these characteristics of color and people's emotion about color to emotion-based digital technologies and their contents, we can effectively draw users' interest and immersion to the contents. In this paper, we will show how people feel about color and present a method of image coloring that reflects the user's preference. First, we define basic templates that reflect the relationship between color and emotion, and then perform an image coloring. To reflect user's preference, we compute weights for hue, saturation and value through the experiments on each subject's preference about hue, saturation and value. The image coloring for each subject's taste will be drawn by updating the weights of hue, saturation and value. Through the results of experiments and surveys, we found that people were more satisfied with the transformation of the templates which reflected user's preference than the one that did not.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.54-61
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• 2009

This paper proposes a skin segmentation method based on region histograms of the color quantization map. First, we make a quantization map of the image using the JSEG algorithm and detect the skin pixel. For the skin region detection, the similar neighboring regions are set by its similarity of the size and location between the previous frame and the present frame from the each region of the color quantization map. Then we compare the similarity of histogram between the color distributions of each quantized region and the skin color model using the histogram distance. We select the skin region by the threshold value calculated automatically. The skin model is updated by the skin color information from the selected result. The proposed algorithm was compared with previous algorithms on the ECHO database and the continuous images captured under time varying illumination for adaptation test. Our approach shows better performance than previous approaches on skin color segmentation and adaptation to varying illumination.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.44-51
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• 2013

Raster operations are widely used to display full-color graphics images (or pixmaps) and single-color images (or bitmaps). These features are strongly needed for image processing applications and font output. However, current mobile graphics platforms, including OpenGL ES hardware implementations, do not directly support these features. To fully support those raster operations on the mobile graphics platforms, we interpreted the graphics images as a set of 3D points, and processed those 3D points through the typical 3D geometry pipelines, in a full-software implementation. Our implementation shows sufficient execution speeds, and passed the official conformance tests to show its correctness.

• The Korean Journal of Nuclear Medicine
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• v.34 no.6
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• pp.439-444
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• 2000

PACS (Picture Archiving and Communication System) is being rapidly spread and installed in many hospitals, but most of the system do not include nuclear medicine field. Although additional costs of hardware for nuclear medicine PACS is low, the complexity in developing viewing software and little market have made the nuclear medicine PACS not popular. Most PACS utilize DICOM 3.0 as standard format, but standard format in nuclear medicine has been Interfile. Interfile should be converted into DICOM format if nuclear images are to be stored and visualized in most PACS. Nowadays, many vendors supply the DICOM option in gamma camera and PET. Several hospitals in Korea have already installed nuclear PACS with DICOM, but only the screen captured images are supplied. Software for visualizing pseudo-color with color lookup tables and expressing with volume view should be developed to fulfill the demand of referring physicians and nuclear medicine physicians. PACS is going to integrate not only radiologic images but also endoscopic and pathologic images. Web and PC based PACS is now a trend and is much compatible with nuclear medicine PACS. Most important barrier for nuclear medicine PACS that we encounter is not a technical problem, but indifference of investor such as administrator of hospital or PACS. Now it is time to support and invest for the development of nuclear medicine PACS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.676-692
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• 2018

Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.