Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform

B-Rep (Boundary Representation) CAD model is widely used in the representation of manufactured product in computer, and it is a kind of real 3D structure with invisible part relative to 2.5D mesh model, so the shape feature recognition of B-Rep model is worth of much studying. We present one approac...

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Main Author: Jihua Wang
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2018/6310482
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spelling doaj-6e52e5cd2f0f4355b4b29de10917b9012020-11-24T21:18:00ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/63104826310482Research on Shape Feature Recognition of B-Rep Model Based on Wavelet TransformJihua Wang0College of Information Science and Engineering, Shandong Normal University, No. 88 Wenhua East Road, Jinan 250014, ChinaB-Rep (Boundary Representation) CAD model is widely used in the representation of manufactured product in computer, and it is a kind of real 3D structure with invisible part relative to 2.5D mesh model, so the shape feature recognition of B-Rep model is worth of much studying. We present one approach of shape feature recognition of B-Rep model based on the wavelet transform of surface boundary and region; it is inspired by the neuropsychology view that surface is the key visual features and by the systematology method that an object is recognized by decomposing and grouping its similar parts. Surface elements of B-Rep model are extracted from the neutral STEP (Standard for Exchange of Product Model Data) file; the curvatures of surface boundary and region were decomposed by wavelet transform, and then the coefficient statistics of same scale were as the surface feature vector. Similar surfaces of B-Rep model were clustered as a bin with the sum of perimeters and the mean vector, and all bins constituting a histogram are finally as the feature vector of B-Rep model. Thus B-Rep models are compared and retrieved using the EMD (Earth Mover’s Distance) of histogram. Our approach was evaluated by retrieval experiment with NDR (National Design Reservoir), and the result indicated its highly competent performance.http://dx.doi.org/10.1155/2018/6310482
collection DOAJ
language English
format Article
sources DOAJ
author Jihua Wang
spellingShingle Jihua Wang
Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
Mathematical Problems in Engineering
author_facet Jihua Wang
author_sort Jihua Wang
title Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
title_short Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
title_full Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
title_fullStr Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
title_full_unstemmed Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform
title_sort research on shape feature recognition of b-rep model based on wavelet transform
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2018-01-01
description B-Rep (Boundary Representation) CAD model is widely used in the representation of manufactured product in computer, and it is a kind of real 3D structure with invisible part relative to 2.5D mesh model, so the shape feature recognition of B-Rep model is worth of much studying. We present one approach of shape feature recognition of B-Rep model based on the wavelet transform of surface boundary and region; it is inspired by the neuropsychology view that surface is the key visual features and by the systematology method that an object is recognized by decomposing and grouping its similar parts. Surface elements of B-Rep model are extracted from the neutral STEP (Standard for Exchange of Product Model Data) file; the curvatures of surface boundary and region were decomposed by wavelet transform, and then the coefficient statistics of same scale were as the surface feature vector. Similar surfaces of B-Rep model were clustered as a bin with the sum of perimeters and the mean vector, and all bins constituting a histogram are finally as the feature vector of B-Rep model. Thus B-Rep models are compared and retrieved using the EMD (Earth Mover’s Distance) of histogram. Our approach was evaluated by retrieval experiment with NDR (National Design Reservoir), and the result indicated its highly competent performance.
url http://dx.doi.org/10.1155/2018/6310482
work_keys_str_mv AT jihuawang researchonshapefeaturerecognitionofbrepmodelbasedonwavelettransform
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