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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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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