• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.79-81
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• 2003

본 논문에서는 위성영상의 강독 분류에 대한 성능 개선을 위하여 ISODATA와 퍼지 C-Means 클러스터링 기법을 이용한 베이시안 최대우도 분류방법을 제안하였다. 본 연구에서는 ISODATA 클러스터링 기법을 이용하여 각각의 분류항목별로 분광특징에 따라 분석가가 선정한 훈련 데이터를 분할하여 새로운 훈련 데이터를 선정함으로써 분류항목별 훈련데이터의 분광적인 특징에 관계없이 분류를 수행할 수 있도록 하였다. 그리고 새롭게 선정된 훈련 데이터를 이용하여 퍼지 C-Means 클러스터링을 수행하고 그 결과를 베이시안 최대우도 분류기법의 사전확률로 이용함으로써 위성영상의 감독 분류에 대한 성능을 개선할 수 있는 방법을 제안한다. 제안된 기법은 Landset TM 위성영상을 이용하여 그 적용성을 시험하였다.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.159-168
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• 2004

This paper presents hybrid classification method to improve the performance of satellite images classification by combining Bayesian maximum likelihood classifier, ISODATA clustering and fuzzy C-Means algorithm. In this paper, the training data of each class were generated by separating the spectral signature using ISODATA clustering. We can classify according to pixel's membership grade followed by cluster center of fuzzy C-Means algorithm as the mean value of training data for each class. Bayesian maximum likelihood classifier is performed with prior probability by result of fuzzy C-Means classification. The results shows that proposed method could improve performance of classification method and also perform classification with no concern about spectral signature of the training data. The proposed method Is applied to a Landsat TM satellite image for the verifying test.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.64-75
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• 2008

Since the current database systems for managing geotechnical investigation results were limited by being described boring test result in point feature, it has been trouble for using other GIS data. Although there are some studies for spatial characteristics of subsurface modeling, it is rather lack of being interoperable with GIS, considering geotechnical engineering facts. This is reason for difficulty of practical uses. In this study, we has developed subsurface spatial information model through extracting needed geotechnical engineering data from geotechnical information DB. The developed geotechnical information clustering program(GEOCL) has made a cluster of boring formation(and formation ratio), classification of layer, and strength characteristics of subsurface. The interpolation of boring data has been achieved through zonal kriging method in the consideration of spatial distribution of created cluster. Finally, we make a subsurface spatial information model to integrate with digital elevation model, and visualize 3-dimensional model by subsurface spatial information viewing program(SSIVIEW). We expect to strengthen application capacity of developed model in subsurface interpretation and foundation design of construction works.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.189-199
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• 2014

Floodplain is a flat plain between levees and rivers. This paper suggests a methodology for analyzing the land uses in the Nakdong River floodplain using the RapidEye imagery and the given LiDAR(LIght Detection And Ranging) DEM(Digital Elevation Models). First, the levee boundaries are generated using the LiDAR DEM, and the area of the floodplain is extracted from the given RapidEye imagery. The land uses in the floodplain are identified in the extracted RapidEye imagery by the ISODATA(Iterative Self-Organizing Data Analysis Technique Analysis) clustering. The overall accuracy of the identified land uses by the ISODATA clustering is 91%. Analysis of the identified land uses in the floodplain is implemented by counting the number of the pixels constituting the land cover clusters. The results of this research shows that the area of the river occupies 46%, the area of the bare soil occupies 36%, the area of the marsh occupies 11%, and the area of the grass occupies 7% in the identified floodplain.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.44-57
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.995-1001
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• 1995

The structure of a typical pattern recognition consists a pre-processing, a feature extraction(algorithm) and classification or recognition. In classification, when widely varying patterns exist in same category, we need the clustering which organize the similar patterns. Clustering algorithm is two approaches. Firs, statistical approaches which are k-means, ISODATA algorithm. Second, neural network approach which is T. Kohonen's LVQ(Learning Vector Quantization). Nikhil R. Palet al proposed the GLVQ(Generalized LVQ, 1993). This paper suggest the efficient feature extraction methods of handwritten numerals in GLVQ clustering network. We use the handwritten numeral data from 21's authors(ie, 200 patterns) and compare the proportion of misclassified patterns for each feature extraction methods. As results, when we use the projection combination method, the classification ratio is 98.5%.

• Journal of the military operations research society of Korea
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• v.26 no.2
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• pp.8-27
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• 2000

This paper evaluates the performance of clustering algorithms in the determination of combat fatigues. Among clustering algorithms, GLVQ in neural clustering methods. and ISODATA algorithm are evaluated in this paper. In order to evaluate, this study used the data sets which showed the body measurement of Korean military personnel. For the comparison of the three methods, the coverage rate and fitness for combat fatigues are evaluated and the convergence of final standard sizes are considered. As a result, the mean of the coverage rate and fitness for combat fatigues obtained with the GLVQ are higher than those obtained with -Means and ISODATA algorithms.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.34-36
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• 2011

ENCs is edited based on the numerical charts for publishing paper charts and serviced in forms of grid styles. For this reason, the density of sounding information of ENCs is not consistent and was required for improvement. In this study, K-Means, ISODATA clustering algorithm as classification methods for satellite image was reviewed and adopted to case study. The developed results include loading module of ENC data, improvement algorithm of sounding information, writing module of ENC data. According to the results of algorithm, we could confirm the improved result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.1-14
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• 2000

The rosette-scan seeker, mounted on the infrared guided missile, is a device that tracks the target It can acquire the 2D image of the target by scanning a space about target in rosette pattern with a single detector Since the detected image is changed according to the position of the object in the field of view and the number of the object is not fixed, the unsupervised methods are employed in clustering it The conventional ISODATA method clusters the objects by using the distance between the seed points and pixels So, the clustering result varies in accordance with the shape of the object or the values of the merging and splitting parameters In this paper, we propose an Array Linkage Clustering Algorithm (ALCA) as a new clustering algorithm improving the conventional method The ALCA has no need for the initial seed points and the merging and splitting parameters since it clusters the object using the connectivity of the array number of the memory stored the pixel Therefore, the ALCA can cluster the object regardless of its shape With the clustering results using the conventional method and the proposed one, we confirm that our method is better than the conventional one in terms of the clustering performance We simulate the rosette scanning infrared seeker (RSIS) using the proposed ALCA as an infrared counter countermeasure The simulation results show that the RSIS using our method is better than the conventional one in terms of the tracking performance.