• Title/Summary/Keyword: Feature Analysis

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Use of Crown Feature Analysis to Separate the Two Pine Species in QuickBird Imagery

  • Kim, Cheon
    • Korean Journal of Remote Sensing
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    • v.24 no.3
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    • pp.267-272
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    • 2008
  • Tree species-specific estimates with spacebome high-resolution imagery improve estimation of forest biomass which is needed to predict the long term planning for the sustainable forest management(SFM). This paper is a contribution to develop crown distinguishing coniferous species, Pinus densiflora and Pinus koraiensis, from QuickBird imagery. The proposed feature analysis derived from shape parameters and first and second-order statistical texture features of the same test area were compared for the two species separation and delineation. As expected, initial studies have shown that both formfactor and compactness shape parameters provided the successful differentiating method between the pine species within the compartment for single crown identification from spaceborne high resolution imagery. Another result revealed that the selected texture parameters - the mean, variance, angular second moment(ASM) - in the infrared band image could produce good subset combination of texture features for representing detailed tree crown outline.

A Study on Fast Matching of Binary Feature Descriptors through Sequential Analysis of Partial Hamming Distances (부분 해밍 거리의 순차적 분석을 통한 이진 특징 기술자의 고속 정합에 관한 연구)

  • Park, Hanhoon;Moon, Kwang-Seok
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.4
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    • pp.217-221
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    • 2013
  • Recently, researches for methods of generating binary feature descriptors have been actively done. Since matching of binary feature descriptors uses Hamming distance which is based on bit operations, it is much more efficient than that of previous general feature descriptors which uses Euclidean distance based on real number operations. However, since increase in the number of features linearly drops matching speed, in applications such as object tracking where real-time applicability is a must, there has been an increasing demand for methods of further improving the matching speed of binary feature descriptors. In this regard, this paper proposes a method that improves the matching speed greatly while maintaining the matching accuracy by splitting high dimensional binary feature descriptors to several low dimensional ones and sequentially analyzing their partial Hamming distances. To evaluate the efficiency of the proposed method, experiments of comparison with previous matching methods are conducted. In addition, this paper discusses schemes of generating binary feature descriptors for maximizing the performance of the proposed method. Based on the analysis on the performance of several generation schemes, we try to find out the most effective scheme.

Numerical Evaluations of the Effect of Feature Maps on Content-Adaptive Finite Element Mesh Generation

  • Lee, W.H.;Kim, T.S.;Cho, M.H.;Lee, S.Y.
    • Journal of Biomedical Engineering Research
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    • v.28 no.1
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    • pp.8-16
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    • 2007
  • Finite element analysis (FEA) is an effective means for the analysis of bioelectromagnetism. It has been successfully applied to various problems over conventional methods such as boundary element analysis and finite difference analysis. However, its utilization has been limited due to the overwhelming computational load despite of its analytical power. We have previously developed a novel mesh generation scheme that produces FE meshes that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with far less number of nodes and elements, thus lessen the computational load. In general, the cMesh generation is affected by the quality of feature maps derived from MRI. In this study, we have tested various feature maps created based on the improved differential geometry measures for more effective cMesh head models. As performance indices, correlation coefficient (CC), root mean squared error (RMSE), relative error (RE), and the quality of cMesh triangle elements are used. The results show that there is a significant variation according to the characteristics of specific feature maps on cMesh generation, and offer additional choices of feature maps to yield more effective and efficient generation of cMeshes. We believe that cMeshes with specific and improved feature map generation schemes should be useful in the FEA of bioelectromagnetic problems.

A Feature-Oriented Requirement Tracing Method with Value Analysis (가치분석을 통한 휘처 기반의 요구사항 추적 기법)

  • Ahn, Sang-Im;Chong, Ki-Won
    • The Journal of Society for e-Business Studies
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    • v.12 no.4
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    • pp.1-15
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    • 2007
  • Traceability links are logical links between individual requirements and other system elements such as architecture descriptions, source code, and test cases. These are useful for requirements change impact analysis, requirements conflict analysis, and requirements consistency checking. However, establishing and maintaining traceability links places a big burden since complex systems have especially yield an enormous number of various artifacts. We propose a feature-oriented requirements tracing method to manage requirements with cost benefit analysis, including value consideration and intermediate catalysis using features. Our approach offers two contributions to the study of requirements tracing: (1)We introduce feature modeling as intermediate catalysis to generate traceability links between user requirements and implementation artifacts. (2)We provide value consideration with cost and efforts to identify traceability links based on prioritized requirements, thus assigning a granularity level to each feature. In this paper, we especially present the results of a case study which is carried out in Apartment Ubiquitous Platform to integrate and connect home services in an apartment complex in details.

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Feature Analysis based on Genetic Algorithm for Diagnosis of Misalignment (정렬불량 진단을 위한 유전알고리듬 기반 특징분석)

  • Ha, Jeongmin;Ahn, Byunghyun;Yu, Hyeontak;Choi, Byeongkeun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.27 no.2
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    • pp.189-194
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    • 2017
  • An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.

A Study on the Improved Post-Analysis Development System in the Naval Combat System

  • Seo, Chang-Won
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.197-207
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    • 2022
  • The Naval Combat System operates in multiple software components for efficient functional processing. Data transmission and reception between components is performed in real time using DDS(Data Distribution Service). Reliable Post-Analysis requires the collection of all DDS messages. However, Software workload and development costs increase because common functions for all messages must be developed directly. In the paper, We propose an improved Post-Analysis based on the Feature Model and a new development system using it. Functions for the modified message were applied as variable domains of the Feature Model. When Build Center updates Post-Analysis, it automatically processes all software tasks associated with Post-Analysis. The proposed development system simplified the overall work procedure, and work time was significantly reduced compared to the existing development system.

Performance Analysis of Feature Detection Methods for Topology-Based Feature Description (토폴로지 기반 특징 기술을 위한 특징 검출 방법의 성능 분석)

  • Park, Han-Hoon;Moon, Kwang-Seok
    • Journal of the Institute of Convergence Signal Processing
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    • v.16 no.2
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    • pp.44-49
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    • 2015
  • When the scene has less texture or when camera pose largely changes, the existing texture-based feature tracking methods are not reliable. Topology-based feature description methods, which use the geometric relationship between features such as LLAH, is a good alternative. However, they require feature detection methods with high performance. As a basic study on developing an effective feature detection method for topology-based feature description, this paper aims at examining their applicability to topology-based feature description by analyzing the repeatability of several feature detection methods that are included in the OpenCV library. Experimental results show that FAST outperforms the others.

The Design of Adaptive Component Analysis System for Image Retrieval (영상 검색을 위한 적응적 컴포넌트 분석 시스템 설계)

  • 최철;박장춘
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.2
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    • pp.19-26
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    • 2004
  • This paper proposes ACA (Adaptive Component Analysis) as a method for feature extraction and analysis of the content-based image retrieval system. For satisfactory retrieval, the features extracted from images should be appropriately applied according to the image domains and for this, retrieval measurement is proposed in this study. Retrieval measurement is a standard indicating how important the value of a relevant feature is to image retrieval. ACA is a middle stage for content-based image retrieval and it purposes to improve the retrieval speed and performance.

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The Design of Adaptive Component Analysis System for Image Retrieval (영상 검색을 위한 적응적 컴포넌트 분석 시스템 설계)

  • 최철;박장춘
    • KSCI Review
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    • v.12 no.1
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    • pp.9-19
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    • 2004
  • This paper proposes ACA (Adaptive Component Analysis) as a method for feature extraction and analysis of the content-based image retrieval system. For satisfactory retrieval, the features extracted from images should be appropriately applied according to the image domains and for this. retrieval measurement is Proposed in this study. Retrieval measurement is a standard indicating how important the value of a relevant feature is to image retrieval ACA is a middle stage for content-based image retrieval and it purposes to improve the retrieval speed and performance.

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Wind-induced vibration characteristics and parametric analysis of large hyperbolic cooling towers with different feature sizes

  • Ke, Shitang;Ge, Yaojun;Zhao, Lin;Tamura, Yukio
    • Structural Engineering and Mechanics
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    • v.54 no.5
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    • pp.891-908
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    • 2015
  • For a systematic study on wind-induced vibration characteristics of large hyperbolic cooling towers with different feature sizes, the pressure measurement tests are finished on the rigid body models of three representative cooling towers with the height of 155 m, 177 m and 215 m respectively. Combining the refined frequency-domain algorithm of wind-induced responses, the wind-induced average response, resonant response, background response, coupling response and wind vibration coefficients of large cooling towers with different feature sizes are obtained. Based on the calculating results, the parametric analysis on wind-induced vibration of cooling towers is carried out, e.g. the feature sizes, damping ratio and the interference effect of surrounding buildings. The discussion shows that the increase of feature sizes makes wind-induced average response and fluctuating response larger correspondingly, and the proportion of resonant response also gradually increased, but it has little effect on the wind vibration coefficient. The increase of damping ratio makes resonant response and the wind vibration coefficient decreases obviously, which brings about no effect on average response and background response. The interference effect of surrounding buildings makes the fluctuating response and wind vibration coefficient increased significantly, furthermore, the increase ranges of resonant response is greater than background response.