• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1099-1101
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• 2003

Change detection technology, which discovers the change information on the surface of the earth by comparing and analyzing multi-temporal satellite images, can be usefully applied to the various fields, such as environmental inspection, urban planning, forest policy, updating of geographical information and the military usage. In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixelbased methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from highresolution satellite images. This system enables fast access to the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1714-1729
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• 2018

Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis. This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM). Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task. The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image. The proposed method has been validated on real bitemporal remote sensing data sets. Experimental results confirmed the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.932-934
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• 2003

In this paper, time, studied about method that can analyze iris change to using differential image of iris image that put interval and films and utilize as patient's health examination according to iris change. Time, Differential mage of iris image that put interval and films ran be used usefully to search early diagnosis of disease and unfolding process etc.. of disease by showing definitely change by tine. In the case of iris diagnostic system, iris outside area extracts iris area and uses Differential image of before filming image and image that film present to use canny edge detector as there is cay to extract iris area as do not help in diagnostic and change analyzed comparison.

• Journal of the Korean association of regional geographers
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• v.5 no.1
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• pp.137-150
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• 1999

Five land use change detection methods were applied to 1994 and 1997 Landsat Thematic Mapper (TM) images of Pook-Gu, Taegu city to determine the land-cover changes between the two dates. The two images were coregistred to UTM coordinates. A post-classification comparison method was the most commonly used quantitative method of change detection. A pre-classification comparison method was more effective method to change detection of land cover than a post-classification comparison method. Two indices were used to assess the accuracies of the studied methods. A image differencing method was found to be most accurate for detecting change verse no change among five land use change detection methods. The difference image of band 2 was found to be most accurate. The overall accuracy and Kappa index agreement of the difference image of band 2 were 0.810 and 0.447.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.367-373
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• 2000

Natural and artificial land features are very dynamic, changing somewhat repidly in our lifetime. It is important that such changes are inventoried accurately so that the physical and human processes at work can be more fully understood. Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. The purpose of this research is to detect environmental changes surrounding an area of Mountain Moscow, Idaho using Landsat Thematic Maper (TM) images of (July 8, 1990 and July 20, 1991). For accurate classification, the Image enhancement process was performed for improving the image quality of each image. A SPOT image (Aug. 14, 1992) was used for image merging in this research. Supervised classification was performed using the maximum likelihood method. Accuracy assessments were done for each classification. Two images were compared on a pixel-by-pixel basis using the post-classification comparison method that is used for detecting the changes of the study area in this research. The 'from-to' change class information can be detected by post classification comparison using this method and we could find which class change to another.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.355-365
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• 2000

The interferometric correlation, or coherence, is calculated to measure the variance of the interferometric phase and amplitude within the neighbourhood of any location within the image at a result of SAR (Synthetic Aperture Radar) interferometric process which utilizes the phase information of the images. The coherence contains additional information that is useful for detecting point targets which change their location in an area of interest (AOI). In this research, a RGB colour composite image was generated with a intensity image (master image), a intensity change image as a difference between master image and slave image, and a coherence image generated as a part of SAR interferometric processing. We developed a technique performing detection of a point target movement using SAR interferometry and applied it to suitable tandem pair images of ERS-1 and ERS-2 as test data. The possibility of change detection of a point target in the AOI could be identified with the technique proposed in this research.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.59-87
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• 2000

The hypothesis of this study is that change acceptance and work adaptation of change agents are influenced by positive self-image and risk tolerance. In order to examine the hypothesis, this study was performed with 305 change agents from six branches of a conglomerate company. Specifically, self-image was measured by locus of control, self-efficacy, self-esteem, and positive affectivity; risk tolerance was measured by tolerance for ambiguity, risk aversion, and openness to experience. The result of this study indicated that self-image and risk tolerance significantly predicted change acceptance and work adaptation. Especially, the results of structural model revealed that change acceptance mediated the relationship between characteristic variables (such as self image and risk tolerance in this study) and work adaptation. Based on the results, we suggest that change agents keep developing positive self-image and risk tolerance in order to play the key role in leading organizational change.

• Survey Research
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• v.1 no.2
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• pp.59-87
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• 2000

The hypothesis of this study is that change acceptance and work adaptation of change agents are influenced by positive self-image and risk tolerance. In order to examine the hypothesis, this study was performed with 305 change agents from six branches of a conglomerate company. Specifically, self-image was measured by locus of control, self-efficacy, self-esteem, and positive affectivity; risk tolerance was measured by tolerance for ambiguity, risk aversion, and openness to experience. The result of this study indicated that self-image and risk tolerance significantly predicted change acceptance and work adaptation. Especially, the results of structural model revealed that change acceptance mediated the relationship between characteristic variables (such as self image and risk tolerance in this study) and work adaptation. Based on the results, we suggest that change agents keep developing positive self-image and risk tolerance in order to play the key role in leading organizational change.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1292-1304
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• 2012

Recently, digital images are extremely forged by editors or advertisers. Also, amateurs can modify images throughout easy editing programs. In this study, we propose identification and analytical methods for the modified images to figure out those problems. In modified image analysis, we classify two parts; a filtering change and a geometric change. Those changes have an algorithm based on interpolation so that we propose the algorithm which is able to analyze a trace on a modified area. With this algorithm, we implement a detection map of interpolation using minimum filter, laplacian algorithm, and maximum filter. We apply the proposed algorithm to modified image and are able to analyze its modified trace using the detection map.

• Journal of IKEEE
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• v.14 no.4
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• pp.291-296
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• 2010

This paper handles, pitching and rolling posture change detection using the visual image changes due to the road slope conditions. When the moving vehicle is slanted to a direction, the objects in the visual images of the vehicle are moving to up or down and right or left. This is similar to the human's balancing behavior depending on the visual image change detection as well as the vestibular organs and semicircular canal in the ear. The proposes method shows the visual image through the camera can be used for the image information itself and for the posture change detection through the experiments.