• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.63-73
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• 1988

In this paper, an algorithm is proposed to evaluate the source-to-terminal reliability, the probability that a source node can communicate with a terminal node, in a probabilistic derected graph. By using Satyanaratana's factoring $theorem^{(7)}$, the original graph can be partitioned into two reduced graphs obtained by contracting and deleting the edge connected to the source node in the probabilistic directed graph. The edge removal proposed in this paper and the general series-parallel reduction can then be applied to the reduced graph. This edge reduction can be applied recursively to the reduced graphs until a source node can be connected to a terminal node by one edge. A computer program which can be applied to evaluating the source-to-terminal reliability in a complex and large network has also been developed.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.74-84
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• 1988

This paper presents feature extraction technique for linear image using edge detection algorithms. The process of edge finding consists of determining edge magnitud and direction by convolution of an image with a number of edge masks, of thinning and ghresholding these edge magnitudes, of linking the edge elemtnts based on proximity ans orientation, and finally, of approximating the linked elements by piede-wise linear segmentss. These techniques are intened to be general and opplications to terminal detection and road recognition tasks are described. The presentation will be helpful to other researchers attempting to implement similar algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.77-80
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• 2006

본 논문에서는 블록 기반의 영상압축에 있어서 선택적 방향성 보간을 이용하는 공간적 에러 은닉 기법을 제안한다. 기존의 공간적 경계 정합 기법은 에지가 단순한 영역에서는 좋은 성능을 보이지만, 손실 블록 내에서 에지의 변화가 큰 영역에서는 좋지 못한 성능을 보인다. 제안된 기법은 이웃한 상하 블록들을 이용하여 에지의 연결성을 추정하고, 이에 따라 공간적 경계정합 기법과 이동 스트라이프 정합 기법을 선택적으로 이용한다. 따라서 에지변화에 적응적으로 대응함으로써 우수한 복원영상을 구할 수 있다. 제안된 기법은 슬라이스 단위의 에러에 대해 적합한 방식으로써, 복잡도가 낮을 뿐만 아니라 객관적 주관적으로 우수한 복원 화질을 얻게 해준다.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.722-725
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• 2009

본 논문에서는 문자인식, 손등 정맥 인식 등에 이용할 수 있는 패턴인식 기법으로 입력된 패턴을 전 처리하여 세선화한 후 유일성이 보장되는 행렬로 변환하는 방법에 관하여 연구 하였다. 입력된 패턴을 세선화 한 후 노드 중심으로 노드에 연결된 에지의 체인 코드와 유크리디안 거리를 노드를 중심으로 가중치와 체인코드를 이용한 행렬을 생성하고, 생성된 행렬의 고유치를 이용하여 인식의 기본 도구로 사용하였다. 이 때 연결된 에지의 방향 코드는 설정된 문턱치 값을 초과하는 변곡에 대하여 새로운 노드를 생성하였다. 이러한 방법을 손등 정맥 패턴 인식에 적용한 결과 인식률이 매우 우수함을 확인할 수 있었다.

• 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 the Korea Society of Computer and Information
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• v.16 no.9
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• pp.69-76
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• 2011

According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

• 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 Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.49-60
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• 2002

We propose an algorithm for extracting the boundary of a desired object with shape information obtained from sample images. Considering global shape obtained from sample images and edge orientation as well as edge magnitude, the Proposed method composed of two steps finds the boundary of an object. The first step is the approximate segmentation that extracts a rough boundary with a probability map and an edge map. And the second step is the detailed segmentation for finding more accurate boundary based on the SEEL (seed-point extraction and edge linking) algorithm. The experiment results using IR images show robustness to low-quality image and better performance than conventional segmentation methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.28-34
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• 2007

A histogram-based road border line extractor is proposed for an efficient road extraction from the high-resolution satellite imagery. The road border lines are extracted from an edge strength map based on the directional histogram difference between the road and the non-road region. The straight and the curved roads are extracted hierarchically from the edge strength map of the original image and the segmented road cluster images, and the road network is constructed based on the connectivity. Unlike the conventional approaches based on the spectral similarity, the proposed road extraction method is more robust to noise because it extracts roads based on the histogram, and is able to extract both the location and the width of roads. In addition, the proposed method can extract roads with various spectral characteristics by identifying the road clusters automatically. Experimental results on IKONOS multi-spectral satellite imagery with high spatial resolution show that the proposed method can extract the straight and the curved roads as well as the accurate road border lines.