• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.132-135
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• 2004

Building information plays a key role in diverse applications such as urban planning, telecommunication and environment monitoring. Automatic building extraction has been a prime interest in the field of GIS and photogrammetry. In this paper, we presented an automatic approach for building extraction from lidar data. The proposed approach is divided into four processes: pre-processing, filtering, segmentation and building extraction. Experimental results showed that the proposed method detected most of buildings with less commission and omission errors.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.216-218
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• 2003

QuickBird satellite is quickly becoming the best choice for high-resolution mapping using satellite images. In this paper, we will describe the followings: (1) how to correct QuickBird data using different geometric correction methods, (2) data fusion using QuickBird panchromatic and multispectral data, and (3) automatic DEM extraction using QuickBird stereo data.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.133-140
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• 2004

A large number of indices are produced from human sensibility ergonomic data, which are accumulated by the project "Study on the Development of Web-Based Database System of Human Sensibility and its Support". Since the research in this field will be increased rapidly, it is necessary to automate the index processing of human sensibility ergonomic data. From the similarity between indexation and summarization, we propose the automation of this process. In this paper, we study on extraction of keywords, information types and expression features that are considered as basic elements of following techniques for automatic summarization: classification of documents, extraction of information types and linguistic features. This study can be applied to automatic summarization system and knowledge management system in the domain of human sensibility ergonomics.rgonomics.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.584-586
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• 2007

3D virtual modeling such as creation of a cyber city or landscape, or making a 3D GIS requires realistic textures. Automatic texture extraction using close range images is not yet efficient or easy in terms of data acquisition and processing. In this paper, common problems associated with automatic texture extraction from aerial photographs are explored. The ZI-buffer, which has depth and facet ID fields, is proposed to remove hidden pixels. The ZI-buffer algorithm reduces memory burden and identifies visible facets. The correct spatial resolution for facet gridding is tested. Error pixels in the visibility map were removed by filtering.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.171-190
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• 2023

This study aims to develop algorithms for automatic extraction landmarks from the lower body of women aged 20-54 using the Grasshopper programming language, based on 3D scan data in the 8th SizeKorea dataset. First, 11 landmarks were defined using the morphological features of 3D body surfaces and clothing applications, from which automatic landmark extraction algorithms were developed. To verify the accuracy of the algorithm, this study developed an additional algorithm that could automatically measure 16 items, and algorithm-derived measurements and SizeKorea measurements were compared using paired t-test analysis. The statistical differences between the scan-derived measurements and the SizeKorea measurements were compared, with an allowable tolerance of ISO 20685-1:2018. This study found that the algorithm successfully identified most items except for the crotch point and gluteal fold point. In the case of landmarks with significant differences, the algorithms were modified. This study was significant because scan editing, landmark search, and measurement extraction were successfully performed in one interface, and the developed algorithm has a high efficiency and strong adaptability.

• Journal of the Ergonomics Society of Korea
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• v.24 no.2
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• pp.35-43
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• 2005

The purpose of this study is to suggest computer assisted neck-base's landmark identification algorithms and measurement extraction methods from three-dimensional human scan data. So we developed the algorithms for automatic identification of landmarks related to the neck-base types. The subjects were 58 women $18{\sim}24$ years of age. Their body were measured directly and indirectly by using camera and three-dimensional body scanner. They were measured during the months of October in 2001. Based on the characters of classified neck-base types, algorithms for the automatic identification of landmarks and methods of automatic measurement are developed. The three-dimensional automatic measuring program is made by $C^{++}$ language. Using this program, 4 landmarks are identified and 6 items are measured. In the verifying the precision of automatic measurement, the height measurements(cervicale, side neck point, front neck point) were relatively accurate, but neck-base width measurement was measured wide.

• Journal of the Society of Disaster Information
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• v.7 no.2
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• pp.140-150
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• 2011

Life Environment is rapidly changing and large scale disasters are increasing from the global warming. Although the disaster repair resources are deployed to the disaster fields, the prevention of the disasters is the most effective countermeasures. the disaster sign data is based on the rule of Heinrich. Automatic extraction of the disaster sign data from the web is the focused issues in this paper. We defined the automatic extraction processes and applied information, such as accident nouns, disaster filtering nouns, disaster sign nouns and rules. Using the processes, we implemented the disaster sign data management system. In the future, the applied information must be continuously updated, because the information is only the extracted and analytic result from the some disaster data.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.