• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.487-498
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• 2005

Recently, It has focused on decision tree algorithm that can handle large dataset. However, because most of these algorithms for large datasets process data in a batch mode, if new data is added, they have to rebuild the tree from scratch. h more efficient approach to reducing the cost problem of rebuilding is an approach that builds a tree incrementally. Representative algorithms for incremental tree construction methods are BOAT and ITI and most of these algorithms use a local discretization method to handle the numeric data type. However, because a discretization requires sorted numeric data in situation of processing large data sets, a global discretization method that sorts all data only once is more suitable than a local discretization method that sorts in every node. This paper proposes an incremental tree construction method that efficiently rebuilds a tree using a global discretization method to handle the numeric data type. When new data is added, new categories influenced by the data should be recreated, and then the tree structure should be changed in accordance with category changes. This paper proposes a method that extracts sample points and performs discretiration from these sample points to recreate categories efficiently and uses confidence intervals and a tree restructuring method to adjust tree structure to category changes. In this study, an experiment using people database was made to compare the proposed method with the existing one that uses a local discretization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1259-1266
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• 2001

최근에 텍스트 압축에 뛰어난 성능을 가지는 블록 정렬 알고리즘인 BW변환 (Burrows-Wheeler Transform)이 소개되었다. 그러나 영상 압축에 BW변환을 직접 적용하면 영상과 텍스트가 갖는 상관성이 서로 다르기 때문에 만족할 만한 압축효과를 기대할 수 없게 된다. 따라서 본 논문에서는 가역의 L-SSKF(Lossless Symmetric Short Kernel Filter)를 사용한 계층적 대역분할로 영상화소 사이의 상관성을 줄인 후 BW변환을 하는 방법과 GAP(Gradient Adjusted Prediction)를 사용하여 LL 대역에 많이 분포된 상관성을 줄인 후 BW변환을 하는 방법을 제안한다. 실험결과 제안한 방법이 기존의 무손실 JPEG 표준안과 LZ 기반의 압축방법(PKZIP) 등에 비해 압축성능이 개선됨을 확인할 수 있었다.

• Journal of the Korea Computer Graphics Society
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• v.15 no.3
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• pp.19-26
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• 2009

In this paper, a new adaptive vertex clustering using a KD-tree is presented for 3D mesh partitioning. A vertex clustering is used to divide a huge 3D mesh into several partitions for various mesh processing. An octree-based clustering and K-means clustering are currently leading techniques. However, the octree-based methods practice uniform space divisions and so each partitioned mesh has non-uniformly distributed number of vertices and the difference in its size. The K-means clustering produces uniformly partitioned meshes but takes much time due to many repetitions and optimizations. Therefore, we propose to use a KD-tree to efficiently partition meshes with uniform number of vertices. The bounding box region of the given mesh is adaptively subdivided according to the number of vertices included and dynamically determined axis. As a result, the partitioned meshes have a property of compactness with uniformly distributed vertices.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.249-258
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• 2002

One of the jai or purposes of multiprocessor system is to get a high efficiency in performance improvement. But in most cases, it is unavoidable to use some special programming languages or tools for full use of multiprocessor system. In general, loop and recursive call statements of algorithms are considered as typical parts for parallelization. Especially, recursive call statements are easy to parallelize conceptually without support of any special languages or tools. But it is difficult to control the degree of parallelism caused by high depth of recursive call leading to execution crash. This paper proposes a device to control Parallelism in the process of POSIX thread bated parallelization of recursive algorithms. For this, we define the concept of thread and process in UNIX system, and analyze the results of experimental application of the device to quick sorting algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.91-96
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• 2010

Concentric mosaics are made with arranging and summing of video frames by using common spacial standards. Compared with previous works on 3-D wavelet transform coding, we have made important design considerations to enable flexible partial decoding and bit-stream random access. A just-in-time(JIT) rendering engine of the compressed concentric mosaic is developed. However, computationally, it is still demanding to accomplish the real-time rendering. Only the contents for specific scene representation are need to be decoded by maintaining compressed data. Thus our proposed algorithm is able to render real concentric mosaic by using lifting scheme instead of wavelet transform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.849-858
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• 2004

Most of supervised teaming algorithms could be applied after that continuous variables are transformed to categorical ones at the preprocessing stage in order to avoid the difficulty of processing continuous variables. This preprocessing stage is called global discretization, uses the class distribution list called bins. But, when data are large and the range of the variable to be discretized is very large, many sorting and merging should be performed to produce a single bin because most of global discretization methods need a single bin. Also, if new data are added, they have to perform discretization from scratch to construct categories influenced by the data because the existing methods perform discretization in batch mode. This paper proposes a method that extracts sample points and performs discretization from these sample points in order to solve these problems. Because the approach in this paper does not require merging for producing a single bin, it is efficient when large data are needed to be discretized. In this study, an experiment using real and synthetic datasets was made to compare the proposed method with an existing one.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.155-162
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• 2008

In this paper we proposed a video watermarking algorithm based on a three dimension discrete wavelet transform (3D DWT) and direct spread spectrum (DSS). In the proposed method, the information watermark is embedded into followed frames, after sync watermark is embedded into the first frame. Input frames are divided into sub frames which are located odd row and even row. The sub frames are arranged as 3D frames, and transformed into 3D wavelet domain. In this domain the watermark is embedded using DSS. Existing video watermarking using 3D DWT is non-blind method but, proposed algorithm uses blind method. The experimental results show that the proposed algorithm is robust against frame cropping, noise addition, compression, etc. acquiring BER of 10% or below and sustains level of 40dB or above on the average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.181-187
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• 2020

In this paper, we proposed a register allocation algorithm and resource allocation algorithm in the high level synthesis process for the SoC design synthesis system of high performance vehicles We have analyzed to the operator characteristics and structure of datapath in the most important high-level synthesis. We also introduced the concept of virtual operator for the scheduling of multi-cycle operations. Thus, we demonstrated the complexity to implement a multi-cycle operation of the operator, regardless of the type of operation that can be applied for commonly use in the resources allocation algorithm. The algorithm assigns the functional operators so that the number of connecting signal lines which are repeatedly used between the operators would be minimum. This algorithm provides regional graphs with priority depending on connected structure when the registers are allocated. The registers with connecting structure are allocated to the maximum cluster which is generated by the minimum cluster partition algorithm. Also, it minimize the connecting structure by removing the duplicate inputs for the multiplexor in connecting structure and arranging the inputs for the multiplexor which is connected to the operators. In order to evaluate the scheduling performance of the described algorithm, we demonstrate the utility of the proposed algorithm by executing scheduling on the fifth digital wave filter, a standard bench mark model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.211-218
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• 2015

This paper introduces a 'divide-and-conquer' algorithm to the travelling salesman problem (TSP). Top 10n are selected beforehand from a pool of n(n-1) data which are sorted in the ascending order of each vertex's distance. The proposed algorithm then firstly selects partial paths that are interconnected with the shortest distance $r_1=d\{v_i,v_j\}$ of each vertex $v_i$ and assigns them as individual regions. For $r_2$, it connects all inter-vertex edges within the region and inter-region edges are connected in accordance with the connection rule. Finally for $r_3$, it connects only inter-region edges until one whole Hamiltonian cycle is constructed. When tested on TSP-1(n=26) and TSP-2(n=42) of real cities and on a randomly constructed TSP-3(n=50) of the Euclidean plane, the algorithm has obtained optimal solutions for the first two and an improved one from that of Valenzuela and Jones for the third. In contrast to the brute-force search algorithm which runs in n!, the proposed algorithm runs at most 10n times, with the time complexity of $O(n^2)$.