• Title/Summary/Keyword: Feature combination

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A Study on Illumination Normalization Method based on Bilateral Filter for Illumination Invariant Face Recognition (조명 환경에 강인한 얼굴인식 성능향상을 위한 Bilateral 필터 기반 조명 정규화 방법에 관한 연구)

  • Lee, Sang-Seop;Lee, Su-Young;Kim, Joong-Kyu
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.4
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    • pp.49-55
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    • 2010
  • Cast shadow caused by an illumination condition can produce troublesome effects for face recognition system using reflectance image. Consequently, we need to separate cast shadow area from feature area for improvement of recognition accuracy. A Bilateral filter smooths image while preserving edges, by means of a nonlinear combination of nearby pixel values. Processing such characteristics, this method is suited to our purpose in illumination estimation process based on Retinex. Therefore, in this paper, we propose a new illumination normalization method based on the Bilateral filter in face images. The proposed method produces a reflectance image that is preserved relatively exact cast shadow area, because coefficient of filter is designed to multiply proximity and discontinuity of pixels in input image. Performance of our method is measured by a recognition accuracy of principle component analysis(PCA) and evaluated to compare with other conventional illumination normalization methods.

Development and Evaluation of a Document Summarization System using Features and a Text Component Identification Method (텍스트 구성요소 판별 기법과 자질을 이용한 문서 요약 시스템의 개발 및 평가)

  • Jang, Dong-Hyun;Myaeng, Sung-Hyon
    • Journal of KIISE:Software and Applications
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    • v.27 no.6
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    • pp.678-689
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    • 2000
  • This paper describes an automatic summarization approach that constructs a summary by extracting sentences that are likely to represent the main theme of a document. As a way of selecting summary sentences, the system uses a model that takes into account lexical and statistical information obtained from a document corpus. As such, the system consists of two parts: the training part and the summarization part. The former processes sentences that have been manually tagged for summary sentences and extracts necessary statistical information of various kinds, and the latter uses the information to calculate the likelihood that a given sentence is to be included in the summary. There are at least three unique aspects of this research. First of all, the system uses a text component identification model to categorize sentences into one of the text components. This allows us to eliminate parts of text that are not likely to contain summary sentences. Second, although our statistically-based model stems from an existing one developed for English texts, it applies the framework to individual features separately and computes the final score for each sentence by combining the pieces of evidence using the Dempster-Shafer combination rule. Third, not only were new features introduced but also all the features were tested for their effectiveness in the summarization framework.

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An Inferencing Semantics from the Image Objects (이미지 객체로부터 의미 정보 추론)

  • Kim, Do-Yeon;Kim, Chyl-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.3
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    • pp.409-414
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    • 2013
  • With the increase of multimedia information such as images, researches have been realized on how to extract the high-level semantic information from low-level visual information, and a variety of techniques have been proposed to generate this information automatically. However, most of these technologies extract the semantic information between single images, it's difficult to extract semantic information when a combination of multiple objects within the image. In this paper, we extract the visual features of objects within the image and training images stored in the DB and the features of each object are defined by measuring the similarity. Using ontology reasoner, each object feature within images infers the semantic information by positional relation and associative relation. With this, it's possible to infer semantic information between objects within images, we proposed a method for inferring more complicated and a variety of high-level semantic information.

Forensic Image Classification using Data Mining Decision Tree (데이터 마이닝 결정나무를 이용한 포렌식 영상의 분류)

  • RHEE, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.7
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    • pp.49-55
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    • 2016
  • In digital forensic images, there is a serious problem that is distributed with various image types. For the problem solution, this paper proposes a classification algorithm of the forensic image types. The proposed algorithm extracts the 21-dim. feature vector with the contrast and energy from GLCM (Gray Level Co-occurrence Matrix), and the entropy of each image type. The classification test of the forensic images is performed with an exhaustive combination of the image types. Through the experiments, TP (True Positive) and FN (False Negative) is detected respectively. While it is confirmed that performed class evaluation of the proposed algorithm is rated as 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic Curve) is 0.9980 by the sensitivity and the 1-specificity. Also, the minimum average decision error is 0.1349. Also, at the minimum average decision error is 0.0179, the whole forensic image types which are involved then, our classification effectiveness is high.

Recognition of damage pattern and evolution in CFRP cable with a novel bonding anchorage by acoustic emission

  • Wu, Jingyu;Lan, Chengming;Xian, Guijun;Li, Hui
    • Smart Structures and Systems
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    • v.21 no.4
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    • pp.421-433
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    • 2018
  • Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.

A Family system of Family Business: Participation within a Family in a Small Family Business (가족기업의 가족체계: 소규모 가족기업에 있어서 가족구성원의 참여유형)

  • 김혜연;김성희
    • Journal of the Korean Home Economics Association
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    • v.38 no.7
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    • pp.1-12
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    • 2000
  • Although the term 'family business' is relatively new, this style of business is universal. An Unusual feature that must be noted, is that even though it is a common style of business is not clearly defined. The purpose of this study is to identify the different family participation patterns, and the variables that effect different types of participation. '1997 Daewoo Panel Data' was used. Some descriptive statistics and a multinomial logit model were employed for the analysis. The standard type of business focused on in this study was a family owned and operated 'ma and pa' typed business and the sample was limited to households where one or both of the partners involved in a family owned and operated business. The main resets obtained from this sample were as follows: 1. Personal characteristics such as respondents' gender, age and educational level were important variables that effected the participation of family members in the business. As can be seen in the gender analysis, family businesses owned by men showed all available patterns of family operated businesses in relatively high numbers. A large percentage of businesses owned women were of self-employed pattern. According to the analysis by age and educational level, young people with a high level of education tend to managed their small businesses by employing others rather than utilising the self-employed or family operated pattern. 2. While big families showed a high percentage of a combination pattern of a family-run, and ordinary employer/employee company, relatively small families usually opted for purely family-run businesses. Whether the family have children under 6 or not, and the number of children under 6 did net significantly effect to the patterns of the family system of small family businesses. 3. The size, location and kind of family business also effected participation patterns of the family members significantly. These results suggest that further study will be required to gain more exact and meaningful information to help Korean family businesses.

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A Study on Adaptive Knowledge Automatic Acquisition Model from Case-Based Reasoning System (사례 기반 추론 시스템에서 적응 지식 자동 획득 모델에 관한 연구)

  • 이상범;김영천;이재훈;이성주
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.81-86
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    • 2002
  • In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.

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Semi-Solid Forming, Casting and Forging Technologies of Lightweight Materials (경량화 소재의 반용융 및 주조/단조기술)

  • 강충길;최재찬;배원병
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.4
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    • pp.7-21
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    • 2000
  • This paper describes an overview of the thixoforming and thixomolding processes. Semi-solid metalworking (SSM), which is called the thixoforming process of aluminium materials, incorporates the elements of both casting and for the manufacture of near net shape parts. The SSM has some advantages such as net shape or near net shape manufacturing, the ability to form thin walls, excellent surface finish, tight tolerance, and excellent dimensional precision. The thixomolding process of Mg alloy (AZ9l) is a combination of two technologies both conventional die casting and plastic injection molding. The feed material used is a machined chip with a geometry of approximately 1 mm square and a length of 2~3 mm. The semi-solid forming (SSF) of high quality aluminium and magnesium parts will be established in the automotive and electronic industry, in the future. The hybrid method of casting/forging has been caused attention. This process uses a preformed material made by casting instead of the wrought material and finishes it by a single forging process. This process is expected to lower costs without sacrificing the mechanical and finishes it by a single forging process. The process is expected to lower costs without sacrificing the mechanical properties. The authors, intending that the casting/forging process contributes to a reduction in production cost of aluminum automotive parts in Korea, describes the feature of the casting/forging process, aluminum alloys suitable for the cast preform, microstructure and mechanical properties of the cast preform, application examples of cast/forging, and further study.

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Development of Operation Scenarios by HILS for the Energy Storage System Operated with Renewable Energy Source (HILS를 이용한 신재생 에너지원이 포함된 에너지 저장시스템의 운영 시나리오 개발)

  • Shin, Dong-Cheol;Jeon, Jee-Hwan;Park, Sung-Jin;Lee, Dong-Myung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.224-232
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    • 2018
  • According to government policy, renewable energy facility such as solar power generation is being implemented for newly constructed buildings. In recent years, the introduction of Energy Storage System (ESS) served as an emergency power for replacing an existing diesel generator has been increasing. Furthermore, in order to expand the efficacy of the ESS operation, operation in combination with renewable energy sources such as solar and wind power generation is increasing. Hence, development of the ESS operation algorithms for emergency mode as well as the peak power cut mode, which is the essential feature of ESS, are necessary. The operational scenarios of ESS need to consider load power requirement and the amount of the power generation by renewable energy sources. For the verification of the developed scenarios, tests under the actual situation are demanded, but there is a difficulty in simulating the emergency operation situation such as system failure in the actual site. Therefore, this paper proposes simulation models for the HILS(Hardware In the Loop Simulation) and operation modes developed through HILS for the ESS operated with renewable energy source under peak power reduction and emergency modes. The paper shows that the ESS operation scenarios developed through HILS work properly at the actual site, and it verifies the effectiveness of the control logic developed by the HILS.

Semi-automatic 3D Building Reconstruction from Uncalibrated Images (비교정 영상에서의 반자동 3차원 건물 모델링)

  • Jang, Kyung-Ho;Jang, Jae-Seok;Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of Korea Multimedia Society
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    • v.12 no.9
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    • pp.1217-1232
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    • 2009
  • In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

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