• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.9-14
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• 2003

The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amounts of spatial data and the imminent need for turning such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. The system is a key section of the research of multi-dimensional and spatio-temporal analysis in the internet environment.

• Spatial Information Research
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• v.19 no.2
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• pp.65-70
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• 2011

Advertizing postal system combined with GIS and temporal/spatial mining techniques has been developed to activate advertizing service and conduct marketing campaign efficiently. In order to select customers accurately, this system provide purchase propensity information using sequential, cyclicpatterns and lifesytle information through RFM analysis and clustering technique. It is possible for corporate mailer to do customer oriented marketing campaign with the advertizing postal system as well as 'one-stop' service including target customer selection, mail production, and delivery request.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.32-134
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• 1998

공간 색인의 하나인 그리드 파일은 공간 데이터 영역을 격자 형태의 셀로 분할하여 구성하는데 특히, 셀들의 크기가 모두 동일한 값으로 고정되어진 것을 고정 그리드(fixed grid)라고 한다. 셀들의 크기가 고정된으로 인해 샐 분할선 상에 객체가 존재하는 경우가 자주 발생하게 되고 이러한 객체들은 하나 이상의 셀에 의해 중복으로 참조된다. 중복 참조 객체는 1/10 시간을 증가시켜 질의 처리 시 성능 저하의 주요한 원인이 된다. 따라서 중복 객체를 효율적으로 처리 할 수 있는 클러스터링 알고리즘의 고안이 필요하다. 이 논문에서는 중복 참조 객체를 처리하기 위한 객체 클러스터링(Object clustering)과 셀 단위로 클러스터하기 위한 셀 클러스터링(Cell clustering) 알고리즘을 구현한다. 그리고 공간 질의 수행 시에 각 클러스터기법들에 대한 성능을 평가한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.567-569
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• 2011

최근 비디오를 즐기는 방법에 있어서 다양한 형식 및 기기가 사용되고 있으며, 이러한 실질적 요구를 충족시키기 위한 방법으로 빠른 비디오 변환 기술이 필요하다. 비디오 변환 기술 중 해상도 축소를 위한 새로운 움직임 벡터 재예측 방법을 제안한다. 줄어든 영상 내 블록의 움직임 벡터를 결정하기 위해 원본 영상 내 대응 되는 위치의 2개 이상의 움직임 벡터들을 K-means clustering 방법 기반으로 다중 후보 움직임 벡터를 결정하고, 결정된 움직임 벡터 중에서 차이의 절대값 합이 최소가 되는 움직임 벡터를 줄어든 영상 내 블록을 위한 움직임 벡터로 결정한다,. 실험 결과 비디오 변환 없이 압축을 수행한 연산시간에 비해 9% 정도의 연산시간이 필요하였으며, 압축 효율은 BR-RATE가 약 17정도 증가하여 기존의 방식의 증가량에 비해 60%로 줄어든 결과를 보여주었다.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.428-431
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• 2004

A multi-stage hierarchical clustering technique, which is an unsupervised technique, has been proposed in this paper for classifying the hyperspectral data .. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using a context-free similarity measure. This study applied the multistage hierarchical clustering method to the data generated by band reduction, band selection and data compression. The classification results were compared with them using full bands.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.150-158
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• 1994

In this paepr, Fuzzy Constraint Line Clustering (FCLC) method for optical flow estimation is proposed. FCLC represents the spatical and temporal gradients as fuzzy sets. Based on these sets, several constraint lines with different membership values are generated for the poxed whose velocity is to be estimated. We describe the process for obtaining the membership values of the spatial and temporal gradients and that of the corresponding constraint line. We also show the process for deciding the tightest cluster of point formalated by intersection between constraint lines. For the synthetic and real images, the results of FCLC are compared with of CLC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.848-854
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• 1996

Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.215-225
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• 2004

A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using the conventional agglomerative approach. Using simulation data, the proposed method was compared with another hierarchical clustering technique based on 'mutual closest neighbor.' The experimental results show that the new approach proposed in this study considerably increases in computational efficiency for larger images with a low number of bands. The technique was then applied to classify the land-cover types using the remotely-sensed data acquired from the Korean peninsula.