• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.73-78
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• 2006

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristic and simplified algorithm. We use topographical features of characters to extract the character points and use MST(Minimum Spanning Tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.441-448
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• 2010

This paper estimates the tree height using Airborne LiDAR that is obtained for each season to analyze its influence based on a canopyclosure and data fusion. The tree height was estimated by extracting the First Return (RF) from the tree and the Last Return (LR) from the surface of earth to assume each tree via image segmentation and to obtain the height of each tree. Each data on tree height that is collected from seasonal data and the result of tree height acquired from the data fusion were compared. A tree height measuring device was used to measure on site and its accuracy was compared. Also, its applicability on the result of fused data that is obtained through the Airborne LiDAR is examined. As a result of the experiment, the result of image segmentation for an individual tree was closer to the result of site study for 1 meter interval when compared to the 0.5 meter interval of point cloud. In case of the tree height, the application of fused data enables a closer site measurement result than the application of data for each season.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.467-469
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• 2003

This research aimed to develop forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data. QuickBird data was used as satellite data. The method of this research was to extract satellite data for every single tree crown using image segmentation technique, then to evaluate the accuracy of classification by changing grouping criteria such as tree species, families, coniferous or broad-leaved species, and timber prices. As a result, the classification of tree species and families level was inaccurate, on the other hand, coniferous or broad-leaved species and timber price level was high accurate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.518-523
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• 2006

Due to keen competition among companies, they have segmented customers and they are trying to offer specially targeted customer by means of the distinguished method. In accordance, data mining techniques are noted as the effective method that extracts useful information. This paper explores customer segmentation of the home study company using a hybrid decision tree and artificial neural network model. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship. The case study shows that the predicted accuracy of the proposed model is higher than those of regression, decision tree (CART), artificial neural networks.

• Health Policy and Management
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• v.12 no.1
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• pp.125-143
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• 2002

The objectives of this study were analysis of patient\`s characteristics and market segmentation in oriental medical care and western medical care. This study focused on medical utilization using Anderson's health utilization model. The source of data was 1998 National Health and Nutrition Survey which Korean Institute For Health and Social Affairs carried out. A stratified multistage probability sampling design was used in this survey. The analysis was conducted using the statistical software package SPSS version 10.0 and Answer Tree 2.1 which is one of data mining methodology. The results were as follows ; 1) 44.9% of respondents reported visiting oriental medical center within recent two weeks. 3.4% of them used oriental medical care. The group of age, kind of disease and medical expenditure are associated with the difference western and oriental medical utilization rate. 2) There were several factors related to utilization of oriental medical care according to decision tree. Especially, important factors that patient chose his medical center were kinds of disease, kinds of common medical use, and expenditure. 3) in the results of CART analysis, market of oriental medical care were classified by seven categories. The major groups who have a preference for oriental medicine were those musculo-skeletal, cerebra-vascular disease, or chronic headache patients, and they had a preference fur oriental medical care in common use. These results show that oriental and western medical market were divided into various areas by market segmentation.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• 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.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.906-909
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• 2000

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristics and simplified algorithm. We use topographical features of characters to extract the character points and use KMST(Kruskal minimum spanning tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.230-235
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• 1998

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.10a
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• pp.61-65
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• 1996

본 논문은, 공간영역에서 화상을 압축할 수 있는 Quad-tree 부호화법을 분석하고, 보다 화질 및 압축율을 개선하기 위하여 적응 불록분할 및 병합 알고리듭을 제안하엿다. 화상은 에지부분을 제외하고는 인접한 화소들간에 데이터의 용장도가 높으므로 이 영역을 하나의 대표값으로 설정하여 그 값과 그 블록의 위치좌표를 부호화할 수 있다. Quad-tree 분할은 초기의 병합을 제외하고 순차적으로 분할과정만 반복처리하지만 본 알고리듬에서는 단위블록(3$\times$3 호소) 의 평균잘류에너지(MRE)를 이용하여 블록의 분할과 병합을 반복처리한다. 시뮬레이션결과, 본 알고리듭은 압축율 1bit/pixel에서 기존의 Quad-tree 방법보다 PSNR에서 1.0dB의 개선이 있었으며, 화상의 블록화 현상도 전혀 나타나지 않았다.