Radial Basis Function for Visual Image Retrieval

被引：0

作者：

Flores-Pulido, Leticia ^{[1
,3
]}

Rodriguez-Gomez, Gustavo ^{[2
]}

Starostenko, Oleg ^{[1
]}

Santacruz-Olmos, Carlos ^{[3
]}

机构：

[1] Univ Americas Puebla, Dept Comp Elect & Mechatron, Sta Catarina Mrtir, Cholula 72820, Mexico

[2] Inst Nacl Astrofis Opt & Electr, Comp Sci Coordinat, Puebla 72000, Mexico

[3] Univ Autonoma Tlaxcala, Engn & Technol Fac, Apizaco Tlax 90300, Mexico

来源：

2010 IEEE ELECTRONICS, ROBOTICS AND AUTOMOTIVE MECHANICS CONFERENCE (CERMA 2010) | 2010年

关键词：

SUBSPACE ARRANGEMENTS;

D O I：

10.1109/CERMA.2010.51

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Visual image retrieval systems imply novel approaches to improve their performance. Search methods require mathematical formalism for feature extraction of multimedial data. Euclidean distance is not enough approach for extracting similarity between images. Radial basis function provides necessary optimization for similarity measures when query image is used as reference. This paper explains a novel method exploiting radial basis function applied for visual image retrieval area. The goal of the approach is the searching process optimization for image retrieval which is obtained results reveal interesting conclusions about advantages of the proposed method even conventional similarity measurement approaches used in content based retrieval area.

引用

页码：383 / 387

页数：5

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