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Author  |
Jon Almazan; Alicia Fornes; Ernest Valveny | ||||
| Title | A Non-Rigid Feature Extraction Method for Shape Recognition | Type | Conference Article | ||
| Year | 2011 | Publication | 11th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 987-991 | ||
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| Abstract | This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. | ||||
| Address | Beijing; China; September 2011 | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-7695-4520-2 | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ AFV2011 | Serial | 1763 | ||
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