• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1391-1394
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• 1997

This paper proposes a new image processing algorithm to recognize korean documents. It take out the region of text area form input image, then it makes esgmentation of lines, words and characters in the text. A precision segmentation is very important to recognize the input document. The input image has 8-bit gray scaled resolution. Not only the histogram but also brightness dispersion graph are used for segmentation. The result shows a higher accuracy of document recognition.

• Journal of the Optical Society of Korea
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• v.4 no.2
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• pp.89-93
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• 2000

Recently a new signal processing algorithm for white light interferometry was presented. In this paper, the proposed signal processing algorithm was applied for absolute temperature measurement using white light interferometry. Stability testing and absolute temperature measurement were demonstrated. Stability test demonstrated the feasibility of absolute temperature measurement with an accuracy of 0.015 fringe. The test also showed that the absolute temperature measurement system using white light interferometry is capable of obtaining the theoretical minimum detectable change (0.0005 fringe), which is consistent with the performance predicted by the proposed signal processing algorithm.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.119-129
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• 1994

This paper describes system and its algorithm which can measure traffic flow on the road by using industrial television applied in industry. This algorithm is using the real-time processing of dynamic scenes. The processing algorithm of dynamic scenes is developed and proved its validity by designing VISC (Video Information Sampler and Converter). The accuracy of this algorithm is enhanced by allocating sampling points in cross-direction of the vehicles.

• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.53-64
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• 2000

With the recent outstanding advance in computer software and hardware, a number of researches to enhance the processing speed and the process accuracy has been undertaken in the field of container terminal industry,0 this paper, we propose a simulator for container image processing that can be used mainly for tile development of automatic container recognition system. The purpose of this study is to simulate many different algorithms and factors to extract information accurately on the captured container image.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1397-1409
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• 2017

For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.396-417
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• 2018

GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.19-27
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• 2021

In this paper, we propose a method for detecting characters in images and detecting facial regions, which consists of two tasks. First, we separate two different characters to detect the face position of the characters in the frame. For fast detection, we use You Only Look Once (YOLO), which finds faces in the image in real time, to extract the location of the face and mark them as object detection boxes. Second, we present three image processing methods to detect accurate face area based on object detection boxes. Each method uses HSV values extracted from the region estimated by the detection figure to detect the face region of the characters, and changes the size and shape of the detection figure to compare the accuracy of each method. Each face detection method is compared and analyzed with comparative data and image processing data for reliability verification. As a result, we achieved the highest accuracy of 87% when using the split rectangular method among circular, rectangular, and split rectangular methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.68-80
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• 2015

To increase the utilization of the KOrea Multi-Purpose SATellite(KOMPSAT) series imagery being developed pursuant to the national space development program, high quality images with enhanced locational accuracy should be created through standardized post-processing processes. In the present study, using the Value-Added Processing System(VAPS) constructed for the post-processing of KOMPSAT imagery, location correction experiments were conducted using KOMPSAT-2 and -3 imagery from domestic and overseas regions. First, 50 pieces from each of KOMPSAT-2 imagery were selected from South Korean and North Korean regions, and modeling was conducted using GCP Chips. According to the results, the Root Mean Square Errors(RMSE) for South Korea and North Korea were 1.59 pixels and 2.04 pixels, respectively, and the locational accuracy of ortho mosaic imagery using check points were 1.33m(RMSE) and 1.90m(RMSE), respectively. Meanwhile, in the case of overseas regions for which GCP could not be easily obtained, the improvement of locational accuracy could be identified through image corrections using Open Street Map(OSM). The VAPS and reference materials used in the present study are expected to be very useful in constructing a precise image DB for entire global regions.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.315-323
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• 2010

In Wireless Sensor Networks (WSNs), various Data-Centric Storages (DCS) schemes have been proposed to store the collected data and to efficiently process a query. A DCS scheme assigns distributed data regions to sensor nodes and stores the collected data to the sensor which is responsible for the data region to process the query efficiently. However, since the whole data stored in a node will be lost when a fault of the node occurs, the accuracy of the query processing becomes low, In this paper, we propose an in-network aggregation query processing method that assures the high accuracy of query result in the case of data loss due to the faults of the nodes in the DCS scheme. When a data loss occurs, the proposed method creates a compensation model for an area of data loss using the linear regression technique and returns the result of the query including the virtual data. It guarantees the query result with high accuracy in spite of the faults of the nodes, To show the superiority of our proposed method, we compare E-KDDCS (KDDCS with the proposed method) with existing DCS schemes without the data-loss correction method. In the result, our proposed method increases accuracy and reduces query processing costs over the existing schemes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.