A RFM Pattern Recognition System Invariant to Rotation, Scale and Translation

被引：0

作者：

Solorza-Calderon, Selene ^{[1
]}

Verdugo-Olachea, Jonathan ^{[1
]}

机构：

[1] Univ Autonoma Baja California, Fac Ciencias, Km 103,Carretera Tijuana Ensenada, Ensenada 22860, Baja California, Mexico

来源：

PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2015 | 2015年 / 9423卷

关键词：

Pattern recognition; Radon-Fourier-Mellin Images; 1D RST invariant signature; Radon transform; Analytical Fourier-Mellin transform;

D O I：

10.1007/978-3-319-25751-8_57

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper a rotation, scale and translation (RST) invariant pattern recognition digital system based on 1D signatures is proposed. The rotation invariance is obtained using the Radon transform, the scale invariance is achieved by the analytical Fourier-Mellin transform and the translation invariance is realized through the Fourier's amplitude spectrum of the image. Once, the RST invariant Radon-Fourier-Mellin (RFM) image is generated (a 2D RST invariant), the marginal frequencies of that image are used to build a RST invariant 1D signature. The Latin alphabet letters in Arial font style were used to test the system. According with the statistical method of bootstrap the pattern recognition system yields a confidence level at least of 95%.

引用

页码：477 / 484

页数：8

共 12 条

[1] Speeded-Up Robust Features (SURF) [J].