Translation and Rotation Invariant Content-based Image Retrieval System

被引：0

作者：

SadegbianNejad, Hossein ^{[1
]}

Shanbehzadeh, Jamsbid ^{[1
]}

Sarafzadeh, Abdolhossein ^{[2
]}

机构：

[1] Tarbiat Moallem Univ Tehran, Tehran, Iran

[2] Unitec, Dept Comp, Auckland, New Zealand

来源：

INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, IMECS 2012, VOL I | 2012年

关键词：

content-based image retrieval; wavelet transform; feature extraction; image processing; SEMANTICS; COLOR; SHAPE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a novel content-based image retrieval algorithm to improve the retrieval performance in situations With local translation and rotation of linage objects. This improvement is the result of employing Frobenius norm of wavelet coefficients. This norm ignores translation and rotation Without negative effects on image object information: This algorithm consists of extracting wavelet coefficients of images and finding their Frobenius norm as the image features. The Frobenius norm of the query image is then compared with the norms of the images in the database. This paper uses the Corel 1000[1, 2] data set images for testing the algorithm. The evaluation criteria are recall rate, precision. and F-Measure.

引用

页码：716 / 719

页数：4

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