• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.48-55
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• 2009

Prior research works in indoor-outdoor classification have been conducted based on a simple combination of low-level features. However, since there are many challenging problems due to the extreme variability of the scene contents, most methods proposed recently tend to combine the low-level features with high-level information such as the presence of trees and sky. To extract these regions from videos, we need to conduct additional tasks, which may yield the increasing number of feature dimensions or computational burden. Therefore, an efficient indoor-outdoor scene classification method is proposed in this paper. First, the video is divided into the five same-sized blocks. Then we define and use the edge and color orientation histogram (ECOH) descriptors to represent each sub-block efficiently. Finally, all ECOH values are simply concatenated to generated the feature vector. To justify the efficiency and robustness of the proposed method, a diverse database of over 1200 videos is evaluated. Moreover, we improve the classification performance by using different weight values determined through the learning process.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.163-168
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• 2022

As cloud computing and the Internet of things are getting popular, the number of devices in the Internet of things computing environments is increasing. In addition, there exist various Internet-based applications, such as home automation and healthcare. In turn, existing studies explored the quality of service, such as downtime and reliability of tasks for Internet of things applications. To enhance the quality of service of Internet of things applications, cloud-fog computing (combining cloud computing and edge computing) can be used for offloading burdens from the central cloud server to edge servers. However, when devices inherit the mobility property, continuity and the quality of service of Internet of things applications can be reduced. In this paper, we propose a resource management scheme based on live migrations for mobility support in edge-based fog computing environments. The proposed resource management algorithm is based on the mobility direction and pace to predict the expected position, and migrates tasks to the target edge server. The performance results show that our proposed resource management algorithm improves the reliability of tasks and reduces downtime of services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.295-301
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• 2018

In various disciplines, researchers, not single researchers, tend to cooperate to study the same topic. There are many studies to analyze the collaborative form of various researchers through the social network analysis method, but there are few such studies in the computer field. In this paper, we analyze the characteristics of network and various groups of researchers through the social network analysis technique of the co-authors of the Journal of Korea Institute of Information and Communication Engineering, and analyze the degree centrality, the between centrality and edge weight. As a result of the analysis, many groups were extracted from the co-author's network, but the top 20 groups accounted for more than 50% of the total, also, we could find a pair of researchers who do joint research with a very high frequency. These Co-author networks are expected to be the basis for in-depth research on the subject and direction of research through future researches.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.43-53
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• 2004

In this paper, we propose a robust deinterlacing algorithm which combines edge dependent interpolation (EDI) and global motion compensation (GMC). Generally, EDI algorithm shows a visually better performance than any other deinterlacing algorithm using one field. However, due to the restriction of information in one field, a high duality progressive image from Interlaced sources cannot be acquired by intrafield methods. On the contrary, since algorithms based on motion compensation make use of not only spatial information but also temporal information, they yield better results than those of using one field. However, performance of algorithms based on motion compensation depends on the performance of motion estimation. Hence, the proposed algorithm makes use of mixing process of EDI and GMC. In order to obtain the best result, an adaptive thresholding algorithm for detecting the failure of GMC is proposed. Experimental results indicate that the proposed algorithm outperforms the conventional approaches with respect to both objective and subjective criteria.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.463-466
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• 2008

With the development of Information Technology in recent years, the image has been an important means to store or express information. Generally, during the process of acquiring and storing images, the images can be corrupted by noise of which typical types are Impulse(Impulse Noise) and AWGN(Addiction White Gaussian Noise). Impulse noise shows irregularly in black and white over the length and breadth of the image by sharp and sudden disturbance of the image signal. In the Impulse noise environment, SM(Standard Median) filter would be used because of its good noise removal performance and simple algorithm. However, when SM filter removes noise, it also produces error at the edge of image and causes whole image quality deterioration. In this paper, we propose a method based on modified nonlinear filter operation scheme which enhances the features of noise removal and detail image preservation when restoring image in Impulse noise environment. And, we compared it with existing methods and the performances through simulation.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.159-169
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• 2003

This paper presents a method for automatic 3-d building reconstruction using high resolution aerial imagery. First, by using edge preserving filtering, noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line segment linking is performed according to direction and length of line segments and the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. Coplanar grouping and pplygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3D building reconstruction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.179-184
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• 2004

This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.605-607
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• 2000

본 논문에서는 유한 필드 GF(2m)상에서 모듈러 곱셈 A(x)B(x) mod p(x)를 수행하는 2-디지트 시리얼 (2-digit-serial) 시스톨릭 어레이 구조인 곱셈기를 제안하였다. LSB-first 곱셈 알고리즘을 분석한 후 2-디지트 시리얼 형태의 자료의존 그래프(data dependency graph, 이하 DG)를 생성하여 시스톨릭 어레이를 설계하였다. 제안한 구조는 정규적이고 서로 반대 방향으로 진행하는 에지들이 없다. 그래서 VLSI 구현에 적합하다. 제안한 2-디지트 시리얼 곱셈기는 비트-패러럴(bit-parallel) 곱셈기 보다는 적은 하드웨어를 사용하며 비트-시리얼(bit-serial) 곱셈기 보다는 빠르다. 본 논문에서 제안한 2-디지트 시리얼 시스톨릭 곱셈기는 기존의 같은 종류의 곱셈기 보다 처리기의 최대 지연 시간이 적다. 그러므로 전체 시스톨릭 곱셈기의 처리시간을 향상시킬 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.667-669
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• 2003

특징 형상의 조합으로 표현될 수 없는 자유 형상을 가진 제품이 늘어남에 따라 자유형상을 효율적으로 변형시키는 기법이 필요하다. 여러 가지 자유형상 변형기법(FFD) 가운데에서 자유 형상을 파라메트릭하게 컨트롤하기 위해서는 조정 다각형 기반의 형상 변형 기법이 적합하다. 이에 따라 본 연구에서는 FFD 기법을 적용하여 자유형상 모델을 파라메트릭하게 컨트롤하기 위해 입력 모델에 대한 조정 다각형을 자동으로 생성하는 알고리즘을 제안하였다. 제안된 알고리즘은 크게 기본 조정 다각형 생성과 조정 다각형 최적화 단계로 나누어진다. 기본 다각형 생성에서는 1)입력모델을 직교 3방향에 투영, 2)투영된 결과에 대해 2차원 조정 다각형을 생성, 3)2차원 조정 다각형을 조합하여 3차원 기본 조정 다각형 생성의 단계를 거친다. 조정 다각형 최적화 단계에서는 기본 조정 다각형에 에지 및 면 연산자를 적용하여 입력 모델에 더욱 근사하는 최종 조정 다각형을 생성한다. 예제에서는 제안된 알고리즘을 통해 자동으로 생성된 조정다각형을 자동차 모델에 적용하여 모델의 형상을 변화시킨 결과를 보였다.