Extraction of Affine Invariant Features Using Fractal
An approach based on fractal is presented for extracting affine invariant features. Central projection transformation is employed to reduce the dimensionality of the original input pattern, and general contour (GC) of the pattern is derived. Affine invariant features cannot be extracted from GC dir...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2013/950289 |
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| _version_ | 1832547021540556800 |
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| author | Jianwei Yang Guosheng Cheng Ming Li |
| author_facet | Jianwei Yang Guosheng Cheng Ming Li |
| author_sort | Jianwei Yang |
| collection | DOAJ |
| description | An approach based on fractal is presented for extracting affine invariant features. Central projection transformation is employed to reduce the dimensionality of the original input pattern, and general contour (GC) of the pattern is derived. Affine invariant features cannot be extracted from GC directly due to shearing. To address this problem, a group of curves (which are called shift curves) are constructed from the obtained GC. Fractal dimensions of these curves can readily be computed and constitute a new feature vector for the original pattern. The derived feature vector is used in question for pattern recognition. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method can be used for object classification. |
| format | Article |
| id | doaj-art-86d34fca18364d429e90f2acc0358839 |
| institution | Kabale University |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-86d34fca18364d429e90f2acc03588392025-02-03T06:46:20ZengWileyAdvances in Mathematical Physics1687-91201687-91392013-01-01201310.1155/2013/950289950289Extraction of Affine Invariant Features Using FractalJianwei Yang0Guosheng Cheng1Ming Li2School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Information Science and Technology, East China Normal University, No. 500, Dong-Chuan Road, Shanghai 200241, ChinaAn approach based on fractal is presented for extracting affine invariant features. Central projection transformation is employed to reduce the dimensionality of the original input pattern, and general contour (GC) of the pattern is derived. Affine invariant features cannot be extracted from GC directly due to shearing. To address this problem, a group of curves (which are called shift curves) are constructed from the obtained GC. Fractal dimensions of these curves can readily be computed and constitute a new feature vector for the original pattern. The derived feature vector is used in question for pattern recognition. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method can be used for object classification.http://dx.doi.org/10.1155/2013/950289 |
| spellingShingle | Jianwei Yang Guosheng Cheng Ming Li Extraction of Affine Invariant Features Using Fractal Advances in Mathematical Physics |
| title | Extraction of Affine Invariant Features Using Fractal |
| title_full | Extraction of Affine Invariant Features Using Fractal |
| title_fullStr | Extraction of Affine Invariant Features Using Fractal |
| title_full_unstemmed | Extraction of Affine Invariant Features Using Fractal |
| title_short | Extraction of Affine Invariant Features Using Fractal |
| title_sort | extraction of affine invariant features using fractal |
| url | http://dx.doi.org/10.1155/2013/950289 |
| work_keys_str_mv | AT jianweiyang extractionofaffineinvariantfeaturesusingfractal AT guoshengcheng extractionofaffineinvariantfeaturesusingfractal AT mingli extractionofaffineinvariantfeaturesusingfractal |