• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.565-569
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• 2007

To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2271-2280
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• 1999

In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.279-287
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• 2009

In this paper, a hierarchical stereo matching with color information is proposed. To generate an initial disparity map, feature based stereo matching is carried out and to generate a final disparity map, hierarchical stereo matching is carried out. The boundary (edge) region is obtained by segmenting a given image into R, G, B and White components. From the obtained boundary, disparity is extracted. The initial disparity map is generated when the extracted disparity is spread to the surrounding regions by evaluating autocorrelation from each color region. The initial disparity map is used as an initial value for generating the final disparity map. The final disparity map is generated from each color region by changing the size of a block and the search range. 4 test images that are provided by Middlebury stereo vision are used to evaluate the performance of the proposed algorithm objectively. The experiment results show better performance compared to the Graph-cuts and Dynamic Programming methods. In the final disparity map, about 11% of the disparities for the entire image were inaccurate. It was verified that the boundary for the non-contiguous point was clear in the disparity map.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.1
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• pp.63-71
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• 1988

In this paper, a fast matching method using hierarchical neighborhood search and subtemplate to reduce very heavy computational load of the conventional matching method, is presented. Some parameters of the proposed method are chosen so that an automatic target tracker to which it is applied can track one moving object well in comparatively simple background. Experimental results show that its performance is not so degraded in spite of high computational reduction over that of the matching method using 3-step search.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.72-78
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• 2017

Prior art search is a core process of technology management performed by inventors and applicants, patent examiners, and employees in the patent industry. As a result of insufficient academic research on a systematic prior art search methodology, the process has been often carried out depending on the subjective judgment of researchers. Previous studies on exploring prior arts based on semantics have also have the risk of underestimating the similarity of major prior arts due to the nature of patent documents where the same technical ideas are expressed in various terms. In this study, we propose an effective prior art search methodology based on hierarchical citation analysis, which provides a clear criterion for selecting core prior arts by calculating weights according to the relative importance of the collected patents. In order to verify the feasibility of the proposed methodology, a case study was conducted to explore the core prior art of one patent in the display field. As a result, 10 core prior art candidates were selected out of the 206 precedent patents.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.8-15
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• 2007

Grid environments provide the mechanism to share heterogeneous resources among nodes. Because of the similarity between grid environments and P2P networks, the structures of P2P networks can be adapted to enhance scalability and efficiency in deployment and to search for services. In this paper, we present a membership management based on a hierarchical ring which constructs P2P-like Grid environments. The proposed approach uses only a limited number of connections, reducing communication cost. Also, it only keeps local information for membership, which leads to a further reduction in management cost. This paper analyzes the performance of the approach by simulation and compares it with other approaches.

• Journal of Information Science Theory and Practice
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• v.5 no.3
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• pp.31-47
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• 2017

The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.