Implicit Moment Invariants

被引：18

作者：

Flusser, Jan ^{[1
]}

Kautsky, Jaroslav ^{[2
]}

Sroubek, Filip ^{[1
]}

机构：

[1] ASCR, Inst Informat Theory & Automat, Prague 18208 8, Czech Republic

[2] Flinders Univ S Australia, Adelaide, SA, Australia

来源：

INTERNATIONAL JOURNAL OF COMPUTER VISION | 2010年 / 86卷 / 01期

关键词：

Invariants; Implicit invariants; Moments; Orthogonal polynomials; Polynomial image deformation; PATTERN-RECOGNITION; IMAGE-ANALYSIS; IDENTIFICATION; NORMALIZATION; REGISTRATION; NOISE;

D O I：

10.1007/s11263-009-0259-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The use of traditional moment invariants in object recognition is limited to simple geometric transforms, such as rotation, scaling and affine transformation of the image. This paper introduces so-called implicit moment invariants. Implicit invariants measure the similarity between two images factorized by admissible image deformations. For many types of image deformations traditional invariants do not exist but implicit invariants can be used as features for object recognition. In the paper we present implicit moment invariants with respect to polynomial transform of spatial coordinates, describe their stable and efficient implementation by means of orthogonal moments, and demonstrate their performance in artificial as well as real experiments.

引用

页码：72 / 86

页数：15

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