• Title/Summary/Keyword: 특징형상

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A Study on the Tolerance Modeler for Feature-based CAPP (특징형상에 기반한 자동공정설계용 공차 모델러 연구)

  • Kim, Jae-Gwan;No, Hyeong-Min;Lee, Su-Hong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.1
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    • pp.48-54
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    • 2002
  • A part definition must not only provide shape information of a nominal part but also contain non-shape information such as tolerances, surface roughness and material specifications. Although machining features are useful for suitable shape information fur process reasoning in CAPP, they need to be integrated with tolerance information for effective process planning. We develop a tolerance modeler that efficiently integrates the machining features with the tolerance information fur feature-based CAPP. It is based on the association of machining features, tolerance features, and tolerances. The tolerance features in this study, where tolerances are assigned, are classified into two types; one type is a face that is a topological entity on a solid model and the other type is a functional geometry that is not referenced to topological entities. The (unctional geometry is represented by using machining features. All the data fur representing the tolerance information are stored completely and unambiguously in an independent tolerance data structure. The developed tolerance modeler is implemented as a module of a comprehensive feature-based CAPP system.

Gesture Recognition using Global and Partial Feature Information (전역 및 부분 특징 정보를 이용한 제스처 인식)

  • Lee, Yong-Jae;Lee, Chil-Woo
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.759-768
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    • 2005
  • This paper describes an algorithm that can recognize gestures constructing subspace gesture symbols with hybrid feature information. The previous popular methods based on geometric feature and appearance have resulted in ambiguous output in case of recognizing between similar gesture because they use just the Position information of the hands, feet or bodily shape features. However, our proposed method can classify not only recognition of motion but also similar gestures by the partial feature information presenting which parts of body move and the global feature information including 2-dimensional bodily motion. And this method which is a simple and robust recognition algorithm can be applied in various application such surveillance system and intelligent interface systems.

Tracking Hand Shape using Active Shape Model and Skin Color Information (능동형상모델과 피부색 검출을 통한 손바닥 경계 형상의 추적)

  • Lee Ju-Young;Kim Jeong-Hyun;Kang Dong-Joong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.05a
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    • pp.681-684
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    • 2006
  • 본 논문은 능동형상모델(Active Shape Model: ASM)을 사용하여 손바닥의 형상을 추출하고 경계형상을 추적하기 위한 방법을 제안한다. 먼저, 경계추적을 위한 초기위치를 입력하기 위해 컬러영상에서 피부색영역의 위치 정보를 통해 중심점을 찾고 그 값을 통해 ASM을 이용하여 손바닥의 영역을 찾는다. ASM은 다양한 경계형상의 학습을 통해 평균값과 형상의 지배적 변형을 나타내는 형상벡터를 추출하기 위한 방법론이며 생체조직과 같은 형상이 일정하지 않고 평균형상을 기준으로 변화하는 형상의 외형을 추출, 추적하기에 적합한 기술이다. 본 논문에서는 피부색 특징을 이용하여 초기 손바닥의 위치를 찾고 이러한 위치정보를 이용하여 손 경계형상의 변화를 추적하는 방법을 실험을 통해 검증하였다

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The Content-Based Image Retrieval by using Color Histogram and Shape-Based Feature Extraction (컬러 히스토그램과 형상 기반 특징 추출을 이용한 내용 기반 영상 검색)

  • Kang, Hyun-Inn;Ju, Yong-Wan;Baek, Kwang-Ryul
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.10
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    • pp.113-122
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    • 1999
  • When we want to retrieve the most similar image from the image database, the color histogram intersection, shape feature and texture feature comparing method are used as a metric to measure the similarity. In order to increase the accuracy of retrievals, we need to integrate two different features. In this paper, the histogram intersection and shape based block histogram intersection method are used. This method results in a high efficient algorithm that meets a similar accuracy and a relatively fast retrieval speed compared to the method of integration of two different features. The Proposed algorithm is tested on retrievals of image database consisting of various 600 images and we implemented that the proposed algorithm gives fast, high efficiency and reliability compared to others.

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Hand Shape Detection and Recognition using Self Organized Feature Map(SOMF) and Principal Component Analysis (자기 조직화 특징 지도(SOFM)와 주성분 분석을 이용한 손 형상 검출 및 인식)

  • Kim, Kyoung-Ho;Lee, Kee-Jun
    • The Journal of the Korea Contents Association
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    • v.13 no.11
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    • pp.28-36
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    • 2013
  • This study proposed a robust detection algorithm. It detects hands more stably with respect to changes in light and rotation for the identification of a hand shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the hand area through pre-processing using a hand shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a hand area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the hand shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

A study on Knowledge based-processing of information to shape cutting (형상 가공 정보의 지식 베이스 처리에 관한 연구)

  • 김희중;조우승;정재현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.970-973
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    • 1995
  • The proposal of this paper is the constructing of knowledge database with manufacturing information. This database contains characteristics of workpiece materials, cutting tools, NC machines, manufacturing processes, and work conditions. And all shape in the system are feature models such base plate, step, hole, pocket, boss, and slot. These information generate a final decision for machining process by the expert system.

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Incremental Feature Recognition from Feature-based Design Model (설계특징형상으로부터 가공특징형상 추출)

  • 이재열;김광수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.737-742
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    • 1994
  • In this paper , we propose an incremental approach for recognizing a class of machining features from a featurebased design model as a part design proceeds, utilizing various information such as nominal geometry, design intents, and design feature characteristics. The proposed apptroach can handle complex intersecting features and protrusion features designed on oblique faces. The class of recognized volumetric machining features can be expressed as Material Removal Shape Element Volumes (MRSEVs), a PDES/STEP-based library of machining features.

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A Study on the relations among the Feature, Function, and Manufacturing Process to integrate the Part Design and Process Planning in the Early Design Stage. (제품개발 초기단계의 제품설계와 공정설계의 통합을 위한 특징형상과 의도기능 및 가공 공정간의 상관 관계에 관한 연구)

  • 임진승;김용세
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.540-545
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    • 2002
  • The tight integration of the part design and process planning is very effective to high quality product development and cost effective manufacturing. Moreover, the integration in the early design stage, that is, the integration of the conceptual design and the conceptual process planning may take a big impact with the forecasting the alternative of the design and manufacturing. In this paper, the real field parts are studied about the relations among the Feature, Function, and Manufacturing Process taking the style of reverse engineering method, to found the base of the systematic computer system for the integrated product design and manufacturing process planning.

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Geometric Feature Recognition Directly from Scanned Points using Artificial Neural Networks (신경회로망을 이용한 측정 점으로부터 특징형상 인식)

  • 전용태;박세형
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.6
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    • pp.176-184
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    • 2000
  • Reverse engineering (RE) is a process to create computer aided design (CAD) models from the scanned data of an existing part acquired using 3D position scanners. This paper proposes a novel methodology of extracting geometric features directly from a set of 3D scanned points, which utilizes the concepts of feature-based technology and artificial neural networks (ANNs). The use of ANN has enabled the development of a flexible feature-based RE application that can be trained to deal with various features. The following four main tasks were mainly investigated and implemented: (1) Data reduction; (2) edge detection; (3) ANN-based feature recognition; (4) feature extraction. This approach was validated with a variety of real industrial components. The test results show that the developed feature-based RE application proved to be suitable for reconstructing prismatic features such as block, pocket, step, slot, hole, and boss, which are very common and crucial in mechanical engineering products.

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