Texture Retrieval System Using Intuitionistic Fuzzy Set Theory

Author

Tripathy, Sanjaya Shankar ; Shekhar, Ravi ; Kumar, R.S.

Author_Institution

Dept. of E.C.E., BIT Mesra, Ranchi, India

fYear

2011

fDate

24-25 Feb. 2011

Firstpage

1

Lastpage

5

Abstract

Fast and accurate image classification is becoming one of the key requirements in content-based image retrieval (CBIR) system. The main idea of CBIR is to search similar image´s based on user query. This paper proposes an improvised texture retrieval system using intuitionistic fuzzy set (IFS) theory. Tamura feature extraction technique is used to extract texture features of each image in the database. The similarity between two images is calculated by using Generalized Tversky´s Index (GTI). Comparing with crisp and fuzzy method, results obtained using IFS were found better because of the consideration of uncertainty.

Keywords

content-based retrieval; feature extraction; fuzzy set theory; image classification; image retrieval; image texture; visual databases; CBIR; GTI; IFS; Tamura feature extraction technique; content based image retrieval; fuzzy method; generalized Tversky Index; image classification; image database; intuitionistic fuzzy set theory; texture retrieval system; Feature extraction; Histograms; Image color analysis; Image retrieval; Indexes; Pragmatics;

fLanguage

English

Publisher

ieee

Conference_Titel

Devices and Communications (ICDeCom), 2011 International Conference on

Conference_Location

Mesra

Print_ISBN

978-1-4244-9189-6

Type

conf

DOI

10.1109/ICDECOM.2011.5738490

Filename

5738490