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Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms.

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Title: Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms.
Authors: Torrente, Maria-Laura1 torrente@dima.unige.it, Biasotti, Silvia1 silvia.biasotti@ge.imati.cnr.it, Falcidieno, Bianca1 bianca.falcidieno@ge.imati.cnr.it
Source: Pattern Recognition. Jan2018, Vol. 73, p111-130. 20p.
Subjects: Hough transforms, Mathematical transformations, Image analysis, Imaging systems, Digital image processing
Abstract: Feature curves are largely adopted to highlight shape features, such as sharp lines, or to divide surfaces into meaningful segments, like convex or concave regions. Extracting these curves is not sufficient to convey prominent and meaningful information about a shape. We have first to separate the curves belonging to features from those caused by noise and then to select the lines, which describe non-trivial portions of a surface. The automatic detection of such features is crucial for the identification and/or annotation of relevant parts of a given shape. To do this, the Hough transform (HT) is a feature extraction technique widely used in image analysis, computer vision and digital image processing, while, for 3D shapes, the extraction of salient feature curves is still an open problem. Thanks to algebraic geometry concepts, the HT technique has been recently extended to include a vast class of algebraic curves, thus proving to be a competitive tool for yielding an explicit representation of the diverse feature lines equations. In the paper, for the first time we apply this novel extension of the HT technique to the realm of 3D shapes in order to identify and localize semantic features like patterns, decorations or anatomical details on 3D objects (both complete and fragments), even in the case of features partially damaged or incomplete. The method recognizes various features, possibly compound, and it selects the most suitable feature profiles among families of algebraic curves. [ABSTRACT FROM AUTHOR]
Copyright of Pattern Recognition is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 125178563
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  Data: Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms.
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  Data: <searchLink fieldCode="AR" term="%22Torrente%2C+Maria-Laura%22">Torrente, Maria-Laura</searchLink><relatesTo>1</relatesTo><i> torrente@dima.unige.it</i><br /><searchLink fieldCode="AR" term="%22Biasotti%2C+Silvia%22">Biasotti, Silvia</searchLink><relatesTo>1</relatesTo><i> silvia.biasotti@ge.imati.cnr.it</i><br /><searchLink fieldCode="AR" term="%22Falcidieno%2C+Bianca%22">Falcidieno, Bianca</searchLink><relatesTo>1</relatesTo><i> bianca.falcidieno@ge.imati.cnr.it</i>
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  Data: <searchLink fieldCode="JN" term="%22Pattern+Recognition%22">Pattern Recognition</searchLink>. Jan2018, Vol. 73, p111-130. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Hough+transforms%22">Hough transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+transformations%22">Mathematical transformations</searchLink><br /><searchLink fieldCode="DE" term="%22Image+analysis%22">Image analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Imaging+systems%22">Imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+image+processing%22">Digital image processing</searchLink>
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  Data: Feature curves are largely adopted to highlight shape features, such as sharp lines, or to divide surfaces into meaningful segments, like convex or concave regions. Extracting these curves is not sufficient to convey prominent and meaningful information about a shape. We have first to separate the curves belonging to features from those caused by noise and then to select the lines, which describe non-trivial portions of a surface. The automatic detection of such features is crucial for the identification and/or annotation of relevant parts of a given shape. To do this, the Hough transform (HT) is a feature extraction technique widely used in image analysis, computer vision and digital image processing, while, for 3D shapes, the extraction of salient feature curves is still an open problem. Thanks to algebraic geometry concepts, the HT technique has been recently extended to include a vast class of algebraic curves, thus proving to be a competitive tool for yielding an explicit representation of the diverse feature lines equations. In the paper, for the first time we apply this novel extension of the HT technique to the realm of 3D shapes in order to identify and localize semantic features like patterns, decorations or anatomical details on 3D objects (both complete and fragments), even in the case of features partially damaged or incomplete. The method recognizes various features, possibly compound, and it selects the most suitable feature profiles among families of algebraic curves. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Pattern Recognition is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.patcog.2017.08.008
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      – Code: eng
        Text: English
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        PageCount: 20
        StartPage: 111
    Subjects:
      – SubjectFull: Hough transforms
        Type: general
      – SubjectFull: Mathematical transformations
        Type: general
      – SubjectFull: Image analysis
        Type: general
      – SubjectFull: Imaging systems
        Type: general
      – SubjectFull: Digital image processing
        Type: general
    Titles:
      – TitleFull: Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms.
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            NameFull: Torrente, Maria-Laura
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            NameFull: Biasotti, Silvia
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            NameFull: Falcidieno, Bianca
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            – D: 01
              M: 01
              Text: Jan2018
              Type: published
              Y: 2018
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              Value: 73
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            – TitleFull: Pattern Recognition
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