• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.171-176
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• 2020

This paper proposes polynomial-time algorithm for maximum weighted independent set(MWIS) problem that is well known as NP-hard. The known algorithms for MWIS problem are polynomial-time to specialized in particular graph type, distributed, or clustering method. But there is no unified algorithm is suitable to all kinds of graph types. Therefore, this paper suggests unique polynomial-time algorithm that is suitable to all kinds of graph types. The proposed algorithm merges the maximum weighted vertex v_i and maximum weighted vertex v_j that is not adjacent to v_i. As a result of apply to undirected graphs and trees, this algorithm can be get the optimal solution. This algorithm improves previously known solution to new optimal solution.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.809-817
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• 2002

This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.239-246
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• 2005

Biologist must have to do 2DGE biological experiment for Protein Search and Analysis. This experiment coming into being 2 dimensional image. 2DGE (2D Gel Electrophoresis : two dimensional gel electrophoresis) image is the most widely used method for isolating of the objective protein by comparative analysis of the protein spot pattern in the gel plane. The process of protein spot analysis, firstly segment protein spots that are spread in 2D gel plane by image processing and can find important protein spots through comparative analysis with protein pattern of contrast group. In the algorithm which detect protein spots, previous 2DGE image analysis is applies gaussian fitting, however recently Watersheds region based segmentation algorithm, which is based on morphological segmentation is applied. Watersheds has the benefit that segment rapidly needed field in big sized image, however has under-segmentation and over-segmentation of spot area when gray level is continuous. The drawback was somewhat solved by marker point institution, but needs the split and merge process. This paper introduces a novel marker search of protein spots by watersheds-based hierarchical threshold, which can resolve the problem of marker-driven watersheds.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.709-721
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• 2009

This paper discusses an efficient image segmentation using morphological watershed algorithm that is robust to noise. Morphological image segmentation consists of four steps: image simplification, computation of gradient image and watershed algorithm and region merging. Conventional watershed segmentation exhibits a serious weakness for over-segmentation of images. In this paper we present a morphological edge detection methods for detecting edges under noisy condition and apply our watershed algorithm to the resulting gradient images and merge regions using Kolmogorov-Smirnov test for eliminating irrelevant regions in the resulting segmented images. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with percentage error as well as computational time needed to segment images. The proposed algorithm can efficiently improve segmentation accuracy and significantly reduce the speed of computational time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1121-1125
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• 2004

This paper is studied the fast block mode decision algorithm for H.264/AVC. The fast block mode decision algorithm is consist of block range decision and merge algorithm. The block range decision algorithm classifies the block over 8$\times$8 size or below for 16$\times$16 macroblock to decide the size and type of sub blocks. The block over 8$\times$8 size is divided into the blocks of 16$\times$8, 8$\times$16 and 16$\times$16 size using merging algorithm which is considered MVD(motion vector difference) of 8$\times$8 block. The sub block range decision reduces encoding arithmetic amount by 48.25% on the average more than the case not using block range decision.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.119-125
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• 2017

In this paper, we propose a method that merges and splits players in the MeanShift tracking framework. The MeanShift tracking moves the center of tracking window to the maximum probability location given the target probability distribution. This tracking method has been widely used for real-time tracking problems because of its fast processing speed. However, it hardly handles occlusions in multiple object tracking systems. Occlusions can be usually solved by applying data association methods. In this paper, we propose a method that can be applied before data association methods. The proposed method automatically merges and splits the overlapped players by adjusting the each player's tracking map. We have compared the tracking performance of the MeanSfhit tracking algorithm and the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.7
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• pp.30-36
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• 2010

Due to the scaling of process parameters, the density on chips has been increasing. This trend increases not only the temperature on chips but also the gradient of the temperature depending on distances. In this paper, we propose the balanced skew tree generation technique for minimizing the clock skew that is affected by the temperature gradients on chips. We calculate the interconnect delay using Elmore delay equation, and find out the optimal balanced clock tree by modifying the clock trees that are generated through the DME(Deferred Merge Embedding) algorithm. We have implemented the proposed technique using C language for the performance evaluation. The experimental results show that the clock insertion point generated by the temperature gradient can be lowered below 54% and we confirm that the skew is remarkably decreased after applying the proposed technique.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.19-27
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.662-668
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• 2001

Since the problem of disproving a tautology is as hard as the problem of proving it, no polynomial time algorithm for falsification(or testing invalidity) is feasible. Previous algorithms are mostly based on either divide-and-conquer or graph representation. Most of them demonstrated satisfactory results on a variety of input under certain constraints. However, they have experienced difficulties dealing with big input. We propose a new falsification algorithm using a Merge Rule to produce a counterexample by constructing a minterm which is not satisfied by an input expression in DNF(Disjunctive Normal Form). We also show that the algorithm is consistent and sound. The algorithm is based on a greedy method which would seek to maximize the number or terms falsified by the assignment made at each step of the falsification process. Empirical results show practical performance on big input to falsify randomized nontautological problem instances, consuming O(nm$^2$) time, where n is the number of variables and m is number of terms.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.123-134
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• 2000

This paper addresses a new triangulation method for constructing surface model from a set of wire-frame contours. The most important problem of contour triangulation is the branching problem, and we provide a new solution for the double branching problem, which occurs frequently in real data. The multiple branching problem is treated as a set of double branchings and an algorithm based on contour merging is developed. Our double branching algorithm is based on partitioning of root contour by Toussiant's polygon triangulation algorithml[14]. Our double branching algorithm produces quite natural surface model even if the branch contours are very complicate in shape. We treat the multiple branching problem as a problem of coarse section sampling in z-direction, and provide a new multiple branching algorithm which iteratively merge a pair of branch contours using imaginary interpolating contours. Our method is a natural and systematic solution for the general branching problem of contour triangulation. The result shows that our method works well even though there are many complicated branches in the object.