Texture retrieval using co-occurrence matrix and symbolic interval data under scale and rotation invariance

Author

De Almeida, Carlos W D ; De Souza, Renata M C R ; Candeias, Ana Lúcia B

Author_Institution

Informatic Center (CIn), Fed. Univ. of Pernambuco, Recife, Brazil

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

2728

Lastpage

2731

Abstract

This article presents a new method for texture description suitable to be used as a solution to the retrieval problem in large image collections. The proposed approach combines multiscalegray-level co-occurrence matrices (GLCM) with Symbolic Data Analysis. A benchmark data set is used to demonstrate the usefulness of the proposed methodology. The experimental results demonstrate that the proposed method is encouraging with an average successful rate of 100% for Dataset 1 and 97.9% for Dataset 2.

Keywords

data analysis; grey systems; image texture; matrix algebra; GLCM; SDA; large image collections; multiscale gray-level co-occurrence matrices; rotation invariance; scale invariance; symbolic data analysis; symbolic interval data; texture description; texture retrieval; Accuracy; Data analysis; Data mining; Equations; Feature extraction; Transforms; GLCM; Scale and rotation invariance; Symbolic interval data; Texture retrieval;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4673-1713-9

Electronic_ISBN

978-1-4673-1712-2

Type

conf

DOI

10.1109/ICSMC.2012.6378160

Filename

6378160