New Method of Primitive Feature Recognition Based on Graphics Comparability

Dimension feature recognition plays an important role in feature recognition in 2D engineering drawings. At present, in most dimension feature recognition methods, the first step is the recognition of whole feature, and then to extract feature information. These methods have some disadvantages, especially in exploded dimension feature recognition. Aimed to solve this problem, this paper introduces a new algorithm of intelligent dimension feature recognition. According to the position relationship with basic elements of dimension, the dimension is recognized in a bottom-up approach. This new method can solves the problem of recognizing the exploded dimension

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View Loops Separation from Engineering Drawings Based on Multi-Granularity Information Acquisition

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.108-111.543 ◽

2010 ◽

Vol 108-111 ◽

pp. 543-548

Author(s):

Jian Ping Liu ◽

Bang Yan Ye ◽

Jian Xi Peng

Keyword(s):

3D Reconstruction ◽

Information Acquisition ◽

Feature Recognition ◽

New Method ◽

Engineering Drawing ◽

Development Tools ◽

Engineering Drawings ◽

Partition Method ◽

Relationship Of ◽

Application Module

To improve the validity and efficiency of feature recognition for 3D reconstruction from engineering drawings, this paper presents a new method of view loops separation based on multi-granularity information acquisition. By analyzing the line-frames of combined primitive views and hidden semantics in engineering drawing, combined relationship of graphics primitives can be identified, then applies line-frames partition method of figuration analysis, view loop separation of individual primitive is realized by inertial loop search with pre-set priority. This algorithm is actualized in AutoCAD 2008 platform with development tools of Object ARX2008 and Visual C#2.0. With this algorithm, an application module of 3D intelligent reconstruction system is developed and finally the validity of this research is verified by examples.

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A Novel Hybrid Design Representation for Automatic Design Features Recognition Systems

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.809-810.847 ◽

2015 ◽

Vol 809-810 ◽

pp. 847-852

Author(s):

Cezary Grabowik ◽

Rafał Zbiciak

Keyword(s):

Product Design ◽

Feature Recognition ◽

Group Technology ◽

Quantitative Description ◽

Design Feature ◽

Qualitative Description ◽

New Method ◽

Automatic Design ◽

Design Representation ◽

Recognition Systems

Problems of design similarity identification and elements grouping play a key factor in the development of design standardization and the group technology methods. Design similarity identification methods are most often based on a comparison of codes ascribed to products design. Basically the code makes a quantitative product description including different product features. Whereas a qualitative description has constituted rather supplement of a quantitative description. The most important issue in a process of design similarity identification is a method of a product design description. This description is usually made with use of special codes composed of alphanumeric characters. The coding process allows reducing the number of data which are being processed during design similarity evaluation, but on the other hand in some cases it could cause information loss. Taking into account above there is still a need of working out of a new method of a product design description which will be able to reduce these negative features of coding techniques. In the paper a novel approach for a product design description is presented. It is proposed to apply a hybrid method for a design representation purpose. This method uses a combination of code chains for a product longitudinal cross-section representation and a spatial matrix for transvers sections. As a result of the conducted research a new method of a product design description was worked out. This method is especially suggested for application in automatic design feature recognition systems (AFR systems) in which a design feature database (DFD) is present.

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Selective Sampling and Orientation of Non-Homogeneous Tissues

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100100238 ◽

1968 ◽

Vol 26 ◽

pp. 98-99

Author(s):

C. C. Clawson ◽

L. W. Anderson ◽

R. A. Good

Keyword(s):

Electron Microscopy ◽

Electron Microscope ◽

Light Microscopy ◽

Random Sampling ◽

New Method ◽

Microscope Examination ◽

Small Areas ◽

Selective Sampling ◽

Large Numbers ◽

Specific Orientation

Investigations which require electron microscope examination of a few specific areas of non-homogeneous tissues make random sampling of small blocks an inefficient and unrewarding procedure. Therefore, several investigators have devised methods which allow obtaining sample blocks for electron microscopy from region of tissue previously identified by light microscopy of present here techniques which make possible: 1) sampling tissue for electron microscopy from selected areas previously identified by light microscopy of relatively large pieces of tissue; 2) dehydration and embedding large numbers of individually identified blocks while keeping each one separate; 3) a new method of maintaining specific orientation of blocks during embedding; 4) special light microscopic staining or fluorescent procedures and electron microscopy on immediately adjacent small areas of tissue.

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