• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1487-1504
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• 1997

In this paper, the two-stage variable block-size multiresolution motion algorithm is proposed for an interframe coding scheme in the wavelet decomposition. An optimal bit allocagion between motion vectors and the prediction error in sense of minimizing the total bit rate is obtained by the proposed algorithm. The proposed algorithm consists of two stages for motion estimatation and only the first stage can be separated and run on its own. The first stage of the algorithm introduces a new method to give the lower bit rate of the displaced frame difference as well as a smooth motion field. In the second stage of the algorithm, the technique is introduced to have more accurate motion vectors in detailed areas, and to decrease the number of motion vectors in uniform areas. The algorithm aims at minimizin gthe total bit rate which is sum of the motion vectors and the displaced frame difference. The optimal bit allocation between motion vectors and displaced frame difference is accomplished by reducing the number of motion vectors in uniform areas and it is based on a botom-up construction of a quadtree. An entropy criterion aims at the control of merge operation. Simulation resuls show that the algorithm lends itself to the wavelet based image sequence coding and outperforms the conventional scheme by up to the maximum 0.28 bpp.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1053-1058
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• 2013

Because of computational burden and complex topology of substation, a transmission overload relief using circuit-breaker switching was very complex and difficult. However, a on-line algorithm for reducing the overloads in transmission lines has made progress due to the advance of IT technology. This paper describes the methodology for alleviating the overloads in transmission lines by circuit-breaker switching. First, the severe contingency lists and substations were selected from the results of contingency analysis. Then the switch combinations are determined using circuit-breakers of the selected substation. The topology changes are limited to equipment outage, bus split, island split, bus merge and island merge. Finally, the fast screening and full analysis methods are used to analyze the overload in transmission lines. To verify the performance of the proposed methodology, we performed a comprehensive test for both test system and large-scale power systems. The results of these tests showed that the proposed methodology can accurately alleviate the overloads in transmission lines from online data and can be applied to on-line applications.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.319-326
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• 2004

In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.249-258
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• 2019

In the cyber-physical system, big data collected from numerous sensors and IoT devices is transferred to the Cloud for processing and analysis. When transferring data to the Cloud, merging data into one single file is more efficient than using the data in the form of split files. However, current merging and splitting operations are performed at the user-level and require many I / O requests to memory and storage devices, which is very inefficient and time-consuming. To solve this problem, this paper proposes kernel-level partitioning and combining operations. At the kernel level, splitting and merging files can be done with very little overhead by modifying the file system metadata. We have designed the proposed algorithm in detail and implemented it in the Linux Ext4 file system. In our experiments with the real Cloud storage system, our technique has achieved a transfer time of up to only 17% compared to the case of transferring split files. It also confirmed that the time required can be reduced by up to 0.5% compared to the existing user-level method.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.523-528
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• 2015

In this paper, we propose a new multiresolutional and dynamic approach of the EM algorithm. EM is a very popular and powerful clustering algorithm. EM, however, has problems that indexes multiresolution data and requires a priori information on a proper number of clusters in many applications, To solve such problems, the proposed EM algorithm can impose a multiresolution kd-tree structure in the E-step and allocates a cluster based on sequential data. To validate clusters, we use a merge criteria for cluster merging. We demonstrate the proposed EM algorithm outperforms for texture image segmentation.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.283-289
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• 2006

The present image segmentation is what user want to segment image and has been studied for technology in composition of segment object with other images. In this paper, we propose a method of novel semi-automatic image segmentation using gradual region merging and genetic algorithm. Proposed algorithm is edge detection of object using genetic algorithm after selecting object which user want. We segment region of object which user want to based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from Segment object. And, we have applicable value which user want by making interface based on GUI for efficient perform of algorithm development. In the experiments, we analyzed various images for proving superiority of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.73-78
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• 2019

This paper proposes polynomial-time rule for maximum weighted independent set(MWIS) problem that is well known NP-hard. The well known distributed algorithm selects the maximum weighted node as a element of independent set in a local. But the merged independent nodes with less weighted nodes have more weights than maximum weighted node are frequently occur. In this case, existing algorithm fails to get the optimal solution. To deal with these problems, this paper constructs maximum weighted independent set in local area. Application result of proposed algorithm to various networks, this algorithm can be get the optimal solution that fail to existing algorithm.

• Journal of KIISE:Software and Applications
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• v.27 no.8
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• pp.804-814
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• 2000

In this paper, we propose an effective method to detect the regions of interests in the Videostrobokymography System. Videostrobokymography system is a medical image processing system for extracting automatically the diagnosis parameters from the irregular vibratory movements of the vocal fold. We detect the regions of interests through three steps. In the first step, we remove the noise in the input image and we find the minimum energy value in each frame. In the second step, we computed the edge by everage value for the one line. In the third step, the regions of interests can be extracted by using the Merge Algorithm which uses the variance of luminance as the feature points. We experimented this method for the vocal fold images of nineteen patients. In consequence, the regions of interests are detected in most vocal fold images. The method proposed in this study is efficient enough to extract the region of interests in the vocal fold images with the frame rate of 40 frames/second and the resolution of 200${\times}$280 pixels.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.601-612
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• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.61-67
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• 2004

We propose a new algorithm to generate additional training patterns using the brain-style information processing algorithm, that is, supervised and unsupervised learning models. This will be useful in the case that we do not have enough number of training patterns because of limitation such as time consuming, economic problem, and so on. We adopt the independent component analysis as an unsupervised model for generating exempalr patterns and multilayer perceptions as supervised models for verifying usefulness of the generated patterns. After statistical analysis of the proposed pattern generation algorithm, we verify successful operations of our algorithm through simulation of handwritten digit recognition with various numbers of training patterns.