Linear feature extraction based on complex ridgelet transform
β Scribed by Xiangqian Jiang; Wenhan Zeng; Paul Scott; Jianwei Ma; Liam Blunt
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 928 KB
- Volume
- 264
- Category
- Article
- ISSN
- 0043-1648
No coin nor oath required. For personal study only.
β¦ Synopsis
In our previous work, a new dual-tree complex wavelet transform (DT-CWT) model for surface analysis has been built, which solved the problem of the lack of shift-invariance that existed in the first and second generation wavelet models. Unfortunately, the DT-CWT model still has the same problem as the previous wavelet models in the lack of ability to detect line singularities or higher dimensional singularities, which causes the edges not to be smooth when extracting the directional features from engineering surfaces.
In this paper, a complex finite ridgelet transform (CFRIT), which provides approximate shift invariance and analysis of line singularities, is proposed by taking the DT-CWT on the projections of the finite Radon transform (FRAT). The Numerical experiments show the remarkable potential of the methodology to analyse engineering and bioengineering surfaces with linear scratches in comparison to wavelet-based methods developed in our pervious work.
π SIMILAR VOLUMES
In this paper, we combine two kinds of features together by virtue of complex vectors and then use the developed generalized K-L transform (or expansion) for feature extraction. The experiments on NUST603 handwritten Chinese character database and CENPARMI handwritten digit database indicate that th
In this paper, we present a feature extraction method by utilizing an error estimation equation based on the Bhattacharyya distance. We propose to use classiΓΏcation errors in the transformed feature space, which are estimated using the error estimation equation, as a criterion for feature extraction