UM
Feature extraction using wavelet and fractal
Tao Y.; Lam E.C.M.; Tang Y.Y.
2001-03-01
Source PublicationPattern Recognition Letters
ISSN01678655
Volume22Issue:3-4Pages:271-287
AbstractIn this paper, we are investigating the utility of several emerging techniques to extract features. A novel method of feature extraction is proposed, which includes utilizing the central projection transformation (CPT) to describe the shape, the wavelet transformation to aid in the boundary identification, and the fractal features to enhance image discrimination. It reduces the dimensionality of a two-dimensional pattern by way of a central projection approach, and thereafter, performs Daubechies' wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform sub-patterns, namely, curves that are non-self-intersecting. The divider dimensions are computed from these curves with a modified box-counting approach. These divider dimensions constitute a new feature vector for the original two-dimensional pattern, defined over the curve's fractal dimensions. We have conducted several experiments in which a set of printed Chinese characters, English letters of varying fonts and other images were classified. Based on the Euclidean distance between the different feature vectors, the experiments have satisfying results. © 2001 Elsevier Science B.V. All rights reserved.
KeywordCentral projection transformation (CPT) Feature extraction Fractal dimension Wavelet transformation
DOI10.1016/S0167-8655(01)00003-4
URLView the original
Language英語
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Cited Times [WOS]:43   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
AffiliationHong Kong Baptist University
Recommended Citation
GB/T 7714
Tao Y.,Lam E.C.M.,Tang Y.Y.. Feature extraction using wavelet and fractal[J]. Pattern Recognition Letters,2001,22(3-4):271-287.
APA Tao Y.,Lam E.C.M.,&Tang Y.Y..(2001).Feature extraction using wavelet and fractal.Pattern Recognition Letters,22(3-4),271-287.
MLA Tao Y.,et al."Feature extraction using wavelet and fractal".Pattern Recognition Letters 22.3-4(2001):271-287.
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