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Research on the Recognition Method of Exploded Dimension Based on 2D Engineering Drawings

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, espe... Full description

Journal Title: Applied Mechanics and Materials 2012, Vol.215, pp.1169-1172
Main Author: Wang, Li Xin
Other Authors: Wang, Yan , Zhou, Jun , Xue, Hui Ling
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 1660-9336 ; E-ISSN: 1662-7482 ; DOI: 10.4028/www.scientific.net/AMM.215-216.1169
Link: http://www.scientific.net/AMM.215-216.1169
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recordid: transtech10.4028/www.scientific.net/AMM.215-216.1169
title: Research on the Recognition Method of Exploded Dimension Based on 2D Engineering Drawings
format: Article
creator:
  • Wang, Li Xin
  • Wang, Yan
  • Zhou, Jun
  • Xue, Hui Ling
subjects:
  • Bottom-Up
  • Dimension
  • Exploded Dimension
  • Feature Recognition
ispartof: Applied Mechanics and Materials, 2012, Vol.215, pp.1169-1172
description: 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
language: eng
source:
identifier: ISSN: 1660-9336 ; E-ISSN: 1662-7482 ; DOI: 10.4028/www.scientific.net/AMM.215-216.1169
fulltext: fulltext
issn:
  • 1660-9336
  • 1662-7482
  • 16609336
  • 16627482
url: Link


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descriptionDimension 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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descriptionDimension 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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abstractDimension 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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doi10.4028/www.scientific.net/AMM.215-216.1169
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date2012-11-15