Blur invariants: A novel representation in the wavelet domain

被引：4

作者：

Makaremi, Iman ^{[1
]}

Ahmadi, Majid ^{[1
]}

机构：

[1] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada

来源：

PATTERN RECOGNITION | 2010年 / 43卷 / 12期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Blur invariant moment; Direct analysis; Feature extraction; Wavelet transform; DEGRADED IMAGE-ANALYSIS; RECOGNITION; SIGNALS;

D O I：

10.1016/j.patcog.2010.07.020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Blur invariants in the wavelet domain are proposed for the first time in this paper. Wavelet domain blur invariants take advantage of several benefits that this domain provides, i.e. different alternatives for wavelet function and analysis in different scales. It is not required to model the blur system in order to extract the invariants. It will be shown how the space domain blur invariants are a special case of the proposed invariants. It will also be explained how the proposed invariants would not have the null space that their special case in the spatial domain have which limits their discriminative power. The performance of these invariants will be demonstrated through experiments, and compared to its counterpart which is defined in the spatial domain. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：3950 / 3957

页数：8

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