Shape matching by part alignment using extended chordal axis transform

One of the main challenges in shape matching is overcoming intra-class variation where objects that are conceptually similar have significant geometric dissimilarity. The key to a solution around this problem is incorporating the structure of the object in the shape descriptor which can be described...

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Vydáno v:Pattern recognition Ročník 57; s. 115 - 135
Hlavní autoři: Yasseen, Z., Verroust-Blondet, A., Nasri, A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.09.2016
Elsevier
Témata:
Algorithms
Chordal axis transform
Computer Science
Dynamic 2D shape segmentation
Dynamic programming
Graphics
Image Processing
Matching
Mathematical analysis
Object recognition
Order disorder
Ordered part correspondence
Salient features
Segmentation
Shape descriptors
Shape matching
Signal and Image Processing
Transforms
Vectors (mathematics)
Salient features
Shape matching
Ordered part correspondence
Shape descriptors
Dynamic programming
Dynamic 2D shape segmentation
Chordal axis transform
ordered part correspondence
dynamic 2D shape segmentation
Chordal Axis Transform
Dynamic Programming
salient features
shape matching
ISSN:0031-3203, 1873-5142
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Popis
Shrnutí:One of the main challenges in shape matching is overcoming intra-class variation where objects that are conceptually similar have significant geometric dissimilarity. The key to a solution around this problem is incorporating the structure of the object in the shape descriptor which can be described by a connectivity graph customarily extracted from its skeleton. In a slightly different perspective, the structure may also be viewed as the arrangement of protruding parts along its boundary. This arrangement does not only convey the protruding part׳s ordering along the anti clockwise direction, but also these parts on different levels of detail. In this paper, we propose a shape matching method that estimates the distance between two objects by conducting a part-to-part matching analysis between their visual protruding parts. We start by a skeleton-based segmentation of the shape inspired by the Chordal Axis Transform. Then, we extract the segments that represent the protruding parts in its silhouette on varied levels of detail. Each one of these parts is described by a feature vector. A shape is thus described by the feature vectors of its parts in addition to their angular and linear proximities to each other. Using dynamic programming, our algorithm finds a minimal cost correspondence between parts. Our experimental evaluations validate the proposition that part correspondence allows conceptual matching of precisely dissimilar shapes. •New concepts employed in skeletonization and segmentation of 2D shapes.•Experimentally weighing geometric properties in visual part salience measure.•Shape retrieval visual parts distance measures rather than boundary points.•A new approach to 2D shape alignment based on part correspondence.
Bibliografie:ObjectType-Article-1
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ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2016.03.022