• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.4 no.2
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• pp.111-116
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• 2000

Transboundary air pollution has recently become an area of increasing scientific interest and political concern as countries are receiving air pollutants from their neighbors. In order to gain a better understanding of the long-range transport processes of air pollutants and the source-receptor relationships among neighboring countries, an atmospheric transport model coupled with a RAMS(Regional Atmospheric Modeling System) model was applied to the East Asia region during the entire month of January 1993. The scalar transport option of the RAMS model was used to calculate special atmospheric constituents such as trace gases or aerosols. The sulfate production in clouds and rainwater and its removal processes by dry and wet deposition were considered. The sulfate budget from source regions to receptor regions was estimated by analysing the source-receptor relationships. When a specific receptor site revealed a sulfate value higher than the sulfate concentration based on its own source origin, this was taken to indicate long-range transport from another source region. The contribution ratio from various source region was calculated. The contribution ratio of dry and wet deposition was higher on the main continent of the East region. Furthermore, the high deposition amounts were identified on the west coast of Korea and the East China Sea.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.592-601
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• 2013

Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.

• Korean Journal of Heritage: History & Science
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• v.48 no.3
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• pp.204-219
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• 2015

International society, including the United Nations, has recently been making efforts to further promote a rapprochement of cultures in relation to alleviating military and political conflicts and other social clashes. In line with these efforts at the international level, there has been a growing interest on Central Asia and, in particular, on the Silk Road, which functioned as a trade route among ancient civilizations in the region and is also seen as a route that promoted cultural dialogue and exchanges. Given the amount of cross cultural dialogue and exchange, it is no surprise that intangible cultural heritage has historically been abundant and easily found in the region. However, this heritage was placed in considerable risk because heritage transmission critically weakened for seventy years under Soviet rule. Fortunately, since independence, there has been increasing interest in restoring community identity and reviving intangible heritage. Nevertheless, in spite of this interest, a lack of policies and cultural support in each country has made heritage safeguarding difficult. In this paper, I analyze the various phenomena that took place after the concept and international trends on ICH were introduced and speak about the experiences and outcomes obtained from collaborative network projects by ICHCAP and the Central Asian countries over the last six year. In addition, I would like take this opportunity to discuss how we can understand and develop collaboration in the intangible heritage field in Central Asia in a long-term perspective.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.526-530
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• 2006

논문은 CT영상에서 영역 확장 기법을 이용하여 인간의 장기 중 뇌와 간을 자동으로 추출할 수 있는 방법을 제안한다. 이는 뇌와 간이 CT영상에서 비교적 넓은 영역을 차지하고 있다는 사실에 기인하였으며, CT영상에서 특정 장기 영역을 추출하기 위해서 크게 초기 탐색 영역 결정 단계와 최종 장기 영역 단계로 나누어진다. 초기 탐색 영역은 CT영상 내에서 추출하고자 하는 장기 영역과 관계없는 부분을 제거하고 특정 장기 영역만을 남겨 관심 장기 영역의 검출률을 높이는 작업이다. 본 논문에서는 CT영상에서 비교적 높은 Gray Level을 가지고 있는 뼈영역인 두개골과 척추의 위치를 기반으로 하여 초기 탐색 영역을 결정하는 방법을 사용하였다. 특정 장기 영역의 추출은 ATID(Automatic Threshold Intensity Decision)를 이용한 이진화 단계, 모폴로지의 Opening 기법을 이용한 잡음제거 단계, Region Growing 기법을 이용한 특정 영역 추출 단계를 이용하는 과정을 거친다. 본 논문에서는 Region Growing 기법을 거친 다음 각각의 그룹 중에서 크기가 가장 큰 부분을 최종 특정 장기 영역으로 결정하였다. 본 논문에서 제안한 알고리즘은 국립전남대학교 부속병원에서 수집된 각각 뇌영상 100장과 간영상 100장을 사용하여 실험하였고, 제안된 알고리즘을 통해 관심 장기 영역을 추출했을 경우 약 91%이상의 높은 추출률을 보였다.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.525-532
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• 2018

Recently, due to the advancements of sensor network technologies and camera technologies, there are increasing needs to effectively monitor the environment in a region that is difficult to access by using the visual sensor network that combines these two technologies. Since the image captured by the visual sensor reflects the natural phenomenon as it is, the quality of the image may deteriorate depending on the weather or time. In this paper, we propose an algorithm to improve the contrast of images using the characteristics of images obtained from visual sensors. In the proposed method, we first set the region of interest and then analyzes the change of the color value of the region of interest according to the brightness value of the image. The contrast of an image is improved by using the high contrast image of the same object and the analysis information. It is shown by experimental results that the proposed method improves the contrast of an image by restoring the color components of the low contrast image simply and accurately.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.253-264
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• 2009

This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.

• Journal of Biomedical Engineering Research
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• v.23 no.1
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• pp.39-47
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• 2002

The objective of this study is to provide a Precise form of spatial normalization with affine transformation. The quantitative comparison of the brain architecture across different subjects requires a common coordinate system. For the common coordinate system, not only global brain but also a local region of interest should be spatially normalized. Registration using mutual information generally matches the whose brain well. However. a region of interest may not be normalized compared to the feature-based methods with the landmarks. The hybrid method of this Paper utilizes feature information of the local region as well as intensity similarity. Central gray nuclei of a brain including copus callosum, which is used for feature in Schizophrenia detection, is appropriately normalized by the hybrid method. In the results section. our method is compared with mutual information only method and Talairach mapping with schizophrenia Patients. and is shown how it accurately normalizes feature .

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3028-3035
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• 2010

This paper propose a genetic method based on probability map to detect region of the lips on a natural image with the faces. The method has many solutions in order to detect regions such as the lips instead of one optimal solution of existing methods. To do this, it represents a pair of spatial coordinates as a chromosome, and introduces genetic operations like conservation interval, the number of generations and non-overlapping selection. By using the probability map of the HS in HSV color space, it increases adaptability to similar color that is a property of genetic algorithm. In our experiments, the optimal value of the important parameter $\beta$ was analyzed, which was used as the condition of an ending function and affected performance of the proposed algorithm. Also the algorithm was analyzed on what performance it has when its mating methods are different. The results of the experiment showed that our algorithm could be flexibly adapted for detecting other ROIs.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.159-175
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• 2015

The two-dimensional QR code has advantages such as directional nature, enough data storage capacity, ability of error correction, and ability of data restoration. There are two major issues like speed and correctiveness of recognition in the two-dimensional QR code. Therefore, this paper proposes a morphology-based algorithm of detecting the interest region of a barcode. Our research contents can be summarized as follows. First, the interest region of a barcode image was detected by close operations in morphology. Second, after that, the boundary of the barcode are detected by intersecting four cross line outside in a code. Three, the projected image is then rectified into a two-dimensional barcode in a square shape by the reverse-perspective transform. In result, it shows that our detection and recognition rates for the barcode image is also 97.20% and 94.80%, respectively and that outperforms than previous methods in various illumination and distorted image environments.