• Title/Summary/Keyword: Object-oriented Classification

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SEGMENTATION-BASED URBAN LAND COVER HAPPING FROM KOMPSAT EOC IMAGES

  • Florian P, Kressler;Kim, Youn-Soo;Klaus T, Steinnocher
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.588-595
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    • 2003
  • High resolution panchromatic satellite images collected by sensors such as IRS-1C/D and KOMPSAT-1 have a spatial resolution of approximately 6 ${\times}$ 6 ㎡, making them very attractive for urban applications. However, the spectral information present in these images is very limited. In order to overcome this limitation, an object-oriented classification approach is used to identify basic land cover types in urban areas. Before an image can be classified it is segmented at different aggregation levels using a multiresolution segmentation approach. In the course of this segmentation various statistical as well as topological information is collected for each segment. Based on this information it is possible to classify image objects and to arrive at much better results than by looking only at single pixels. Using an image recorded by KOMPSAT-1 over the City of Vienna a land cover classification was carried out for two areas. One was used to set up the rules for the different land cover types. The second subset was classified based on these rules, only adjusting some of the functions governing the classification process.

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Basal Area Mapping using Remote Sensing and Ecological Data (원격 탐사 자료와 현장 조사 자료를 이용한 기저면적 예측 지도 제작)

  • Lee, Jung-Bin;Jayakumar, S.;Heo, Joon
    • Korean Journal of Remote Sensing
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    • v.24 no.6
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    • pp.621-629
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    • 2008
  • This study was carried out in part of Tamil Nadu, India. Also, Landsat ETM+ image and field sampling data were acquired. The field data were basal area, number of trees and number of species. Using the data set, this study performed a three steps processing, (1) Image classification (2) extracting the vegetation indices(NDVI, Tasseled cap brightness, greenness and wetness) (3) mapping the prediction of biodiversity distribution using basal area and NDVI image value. Basal area was significantly correlated with NDVI. The result of classification showed 69% overall accuracy.

Service Identification of Component-Based For Extending Service-Oriented Computing System (서비스지향 컴퓨팅 시스템으로의 확장을 위한 컴포넌트 기반의 서비스 식별)

  • Choi, Mi-Sook;Lee, Seo-Jeong;Lee, Jong-Suk;Yang, Seung-Won
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.710-727
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    • 2008
  • Service-oriented computing systems have been issued by their properties of reducing software development time and effort by reusing functional service units. The reusability of services can effectively promote through loose coupling between services. But strong associations of object-oriented systems such as inheritance and aggregation create a rather tight coupling between objects. The component-based systems without inheritance and aggregation create a loose coupling between components. Thus components provide service realization at runtime using the functionality provided by their interfaces. Therefore legacy component-based systems need to have service-oriented computing concept in order to support functional service units efficiently. Also, conventional methods for service-oriented computing system have not suggested the clear classification of service layers, the clear service identification guideline introducing service layers and a service mapping method between serviceces of each layer. Therefore we suggest the service classification and the identification guideline of business view and implementation view introducing layers and propose a mapping between two views. That is, we research service layers, service identification, diversified service sizes and a service mapping method between services of each layer. This can be applied to legacy component-based system to extend to the service-oriented computing system.

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Comparative Research of Image Classification and Image Segmentation Methods for Mapping Rural Roads Using a High-resolution Satellite Image (고해상도 위성영상을 이용한 농촌 도로 매핑을 위한 영상 분류 및 영상 분할 방법 비교에 관한 연구)

  • CHOUNG, Yun-Jae;GU, Bon-Yup
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.3
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    • pp.73-82
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    • 2021
  • Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

Library Management and Services for Software Component Reuse on the Web (Web 소프트웨어 컴포넌트 재사용을 위한 라이브러리 관리와 서비스)

  • Lee, Sung-Koo
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.10-19
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    • 2002
  • In searching and locating a collection of components on the Web, users require a Web browser. Since the Web libraries tend to grow rapidly, there needs to be an effective way to organize and manage such large libraries. Traditional Web-based library(retrieval) systems provide various classification scheme and retrieval services to store and retrieve components. However, these systems do not include invaluable services, for example, enabling users to grasp the overall contents of the library at the beginning of retrieval. This paper discusses a Web-based library system, which provides the efficient management of object-oriented components and a set of services beyond simple component store and retrieval. These services consist of component comprehension through a reverse engineering process, automated summary extraction, and comprehension-based retrieval. Also, The performance of an automated cluster-based classification scheme adopted on the system is evaluated and compared with the cluster-based classification scheme adopted on the system is evaluated and compared with the performance of two other systems using traditional classification scheme.

Applying Meta-model Formalization of Part-Whole Relationship to UML: Experiment on Classification of Aggregation and Composition (UML의 부분-전체 관계에 대한 메타모델 형식화 이론의 적용: 집합연관 및 복합연관 판별 실험)

  • Kim, Taekyung
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.99-118
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    • 2015
  • Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

Sign Language Translation Using Deep Convolutional Neural Networks

  • Abiyev, Rahib H.;Arslan, Murat;Idoko, John Bush
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.631-653
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    • 2020
  • Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

A Study on Service R&D Budgeting and Investment Strategy (서비스 R&D 예산편성 및 투자전략 연구)

  • Kim, Hyunsoo
    • Journal of Information Technology Services
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    • v.12 no.2
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    • pp.373-386
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    • 2013
  • The purpose of this research is to develop a model for efficient service R&D investment in government budgeting process. It is necessary to develop an efficient and effective investment model to improve competitiveness of the service industry and national economy. Various existing types of service R&D classification have been reviewed. And object-oriented service R&D request classification types have been derived. A tentative model for evaluating service R&D requests have been developed through extensive discussions on effective methodologies. The model has been refined and revised by four service budgeting experts. The revised and refined checklists and guidelines have been used for 40 real service R&D requests evaluations. As a result, a full model for service R&D evaluation and budgeting has been proved to be useful. Also, a need for more efficient and concise evaluation model has been raised through this evaluation process. A brief model with only 10 checklists has been developed and its usefulness has been proven by pilot test with 10 real service R&D requests. The results of this study can be used for evaluation of service R&D proposals and effective budgeting of R&D requests for improving global competitiveness. Further research is needed for refining the developed evaluation models.

MAPPING OF EUCALYPTUS PLANTATIONS THROUGH TEMPORAL SATELLITE DATA IN CHINA

  • Heo, Joon;Jayakumar, S.;Lee, Jung-Bin
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.471-474
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    • 2007
  • Eucalyptus plantations play a major role in the China's ecological, social, economic and other aspects and presently China is the second largest producer of Eucalyptus in the world next to Brazil. It was introduced as an ornamental tree during 1890 but later it became a commercial crop. During 1960s large number of Eucalyptus timber were used for railway sleepers and it was also used as shelter belt for rubber trees. It becomes one of the important national resources of commercial timber once the production reached to 5 million $m^{3}/yr$. Through Eucalyptus oil, it brought about 20% of foreign exchange. In the present study, it was aimed to estimate the Eucalyptus growing area in the southern Guangdong in China in terms of aerial extent and changes between 1991 and 2001 using Landsat TM and ETM+ data. Object based classification technique and subsequent temporal change detection analysis were followed to identify the changes between the periods. In the present study, the total area was divided into three classes viz., plantation area with trees, plantation area without trees and others. Object oriented classification was found to be more accurate in the present study. Overall increase of about 23.62 $km^{2}$ was noted between 1991 and 2001 in the plantation area. With reference to the present study area, the growth of Eucalyptus growing area was 7.4% in the 10 year periods. From this study it is clear that the area under Eucalyptus cultivation is growing considerably year by year in China. However, elaborate study must be conducted considering larger areas to accurately predict the growth of Eucalyptus growing areas.

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Comparison of object oriented and pixel based classification of satellite data for effective management of natural resources (천연 자원의 효율적인 관리를 위한 위성자료의 객체 및 픽셀기반의 비교)

  • Jayakumar, S.;Heo, Joon;Sohn, Hong-Gyoo;Lee, Jung-Bin;Kim, Jong-Suk
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.215-218
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    • 2007
  • 이 논문은 고해상도 Quickbird 영상을 이용하여 세부레벨계획을 위한 토지피복분류를 수행하였으며 고해상도 영상을 이용한 토지피복분류를 위하여 객체기반분류와 ISODATA 기법을 적용하였다. 객체기반분류는 eCognition 소프트웨어를 사용하였으며 ISODATA 기법의 토지피복분류 결과와 비교분석을 수행하였다. 연구 대상지역은 인도의 Sukkalampatti이라 하는 작은 유역을 대상으로 연구를 진행하였다. 고해상도 영상의 사용으로 토지피복분류에 있어서 공간 해상도에 따른 토지피복의 세부레벨분류 정확도를 향상 시킬 수 있는 이점을 확인 할 수 있으며 또한, 객체기반분류와 ISODATA 기법의 분류 결과는 eCognition을 사용한 객체기반 토지피복분류결과가 ISODATA의 픽셀기반의 분류방법보다 높은 정확도를 보였다.

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