• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.63-68
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• 2009

The location of mobile terminals in cellular networks is an important problem in the field of information technology with applications in resource allocation, location sensitive browsing, and emergency communications. Finding location estimation techniques that are robust to non-line of light (NLOS) propagation is a key problem in this area. Time of arrival (TOA) and pattern matching (PM) measurements can be made simultaneously by CDMA cellular networks at low cost. The different sources of errors for each measurement type cause TOA and PM measurements to contain independent information about mobile station (MS) locations. This paper combines the information of PM and TOA measurements to calculate a superior location estimate. The proposed location estimator is robust, provides lower error than the estimators based on the individual measurements, and has low implementation costs.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.22 no.2
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• pp.91-100
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• 2018

In this paper, we propose a new method for template matching, patch ratio, to inpaint unknown pixels. Before this paper, many inpainting methods used sum of squared differences(SSD) or sum of absolute differences(SAD) to calculate distance between patches and it was very useful for closest patches for the template that we want to fill in. However, those methods don't consider about geometric similarity and that causes unnatural inpainting results for human visuality. Patch ratio can cover the geometric problem and moreover computational cost is less than using SSD or SAD. It is guaranteed about finding the most similar patches by Cauchy-Schwarz inequality. For ignoring unnecessary process, we compare only selected candidates by priority calculations. Exeperimental results show that the proposed algorithm is more efficent than Criminisi's one.

• Journal of IKEEE
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• v.22 no.3
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• pp.882-885
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• 2018

Recently, signal integrity on PCB (printed circuit board) becomes very important as the system operation speed increases. So far, PCB is customarily designed to minimize area and cost. However, ultra-high-speed PCB often fail to operate properly, unless it is precisely and carefully designed considering dielectric characteristics, line width, line spacing, and impedance matching. This paper surveys many problems in ultra-high-speed PCB and various design methods to mitigate them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2173-2193
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• 2013

In order to reduce the distribution cost of sensor nodes, a mobile sensor deployment has been proposed. The mobile sensor deployment can be solved by finding the optimal layout and planning the movement of sensor nodes with minimum energy consumption. However, previous studies have not sufficiently addressed these issues with an efficient way. Therefore, we propose a new deployment approach satisfying these features, namely a tree-based approach. In the tree-based approach, we propose three matching schemes. These matching schemes match each sensor node to a vertex in a rake tree, which can be trivially transformed to the target layout. In our experiments, the tree-based approach successfully deploys the sensor nodes in the optimal layout and consumes less energy than previous works.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.529-532
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• 1988

This paper proposes a graph matching algorithm based on simulated annealing, which assures the globally optimal solution for circuit partitioning for the placement in the rectilinear region occurring as a result of the pre-placement of some macro cells, or onto the nonplanar surface in some military or space applications. The circuit graph ($G_{C}$) denoting the circuit topology is formed by a hierarchical bottom-up clustering of cells, while another graph called region graph ($G_{R}$) represents the geometry of a planar rectilinear region or a nonplanar surface for circuit placement. Finding the optimal many-to-one vertex mapping function from $G_{C}$ to $G_{R}$, such that the total mismatch cost between two graphs is minimal, is a combinatorial optimization problem which was solved in this work for various examples using simulated annealing.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.805-807
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• 2005

본 논문에서는 동적 계획법(dynamic programming)과 이미지 세그먼트(segment)를 이용한 새로운 스테레오 정합(stereo matching)기법을 제안한다. 일반적으로 동적 계획법(dynamic programming)은 빠르면서도 비교적 정확하고, 조밀(dense)한 disparity map을 얻을 수 있다. 그러나 경계(boundary)근처의 폐색지역(occlusion region)이나, 텍스쳐가 적은 모호한 영역에서는 잘못된 결과를 유도할 수 있다. 본 논문에서는 이러한 문제점들을 해결하기 위해 먼저 이미지를 아주 작은 영역으로 분할(over-segmentation)하고, 이런 작은 영역들이 비슷한 disparity를 가질 것이라고 가정한다. 다음으로 동적 계획법(dynamic programming)을 통해 정합을 수행한다. 여기서 계산비용(cost)은 기존의 정합윈도우 안에서 세그먼트 영역을 적용한 새로운 비용함수를 사용하며, 이 새로운 비용함수를 통해 정확도를 높인다. 마지막으로 동적 계획법을 통하여 얻어진 조밀한 disparity map을 세그먼트 영역들의 시각특성(visibility)과 유사도(similarity)를 이용하여 에러를 찾아내고, 세그먼트 정합을 통해 수정함으로 정확한 disparity map을 찾아낸다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.53-62
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• 1998

In this paper, a genetic algorithm-based optimization technique for stereo matching is proposed. Stereo matching is an essential process to recover three-dimensional structure of objects. The proposed two-dimensional chromosomes consist fo disparity values. The cost function of each chromosome is composed of the intensity-difference between two images and smoothness of disparity. The crossover and mutation operators in the two-dimensional chromosomes are described. The operations are affected by the disparities of neighbor pixels. The knowledge-augmented operators are shown to result in rapid convergence and stable result. The genetic algorithm for stereo matching is tested on synthetic and natural images. Experimental results of various images show that the proposed algorithm has good performance even if the images have too dense or sparse feature points. severe noise, and repeating pattern.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.145-156
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• 2007

Recently, the needs for effective real time change detection algorithms for XML/HTML documents and increased in such fields as the detection of defacement attacks to web documents, the version management, and so on. Especially, those applications of real time change detection for large number of XML/HTML documents require fast heuristic algorithms to be used in real time environment, instead of algorithms which compute minimal cost-edit scripts. Existing heuristic algorithms are fast in execution time, but do not provide satisfactory edit script. In this paper, we present existing algorithms XyDiff and X-tree Diff, analyze their problems and propose algorithm X-tree Diff which improve problems in existing ones. X-tree Diff+ has similar performance in execution time with existing algorithms, but it improves matching ratio between nodes from two documents by refining matching process based on the notion of efficiency of matching.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.517-526
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• 2008

Stereo vision is a fundamental method for measuring 3D structures by observing them from two cameras placed on different positions. In order to reconstruct 3D structures, it is necessary to create a disparity map from a pair of stereo images. To create a disparity map we compute the matching cost for each point correspondence and compute the disparity that minimizes the sum of the whole matching costs. In this paper, we propose a method to estimate a dense disparity map using region segmentation. We segment each scanline using region homogeneity properties. Using the segmented regions, we prohibit false matches in the stereo matching process. Disparities for pixels that failed in matching are filled by interpolating neighborhood disparities. We applied the proposed method to various stereo images of real environments. Experimental results showed that the proposed method is stable and potentially viable in practical applications.