Brain image retrieval using Local Ternary Co-Occurrence Pattern and CDF 9/7 wavelet

Author

Anju, T.A. ; Chandy, D. Abraham

Author_Institution

Dept. of ECE, Karunya Univ., Coimbatore, India

fYear

2014

fDate

13-14 Feb. 2014

Firstpage

1

Lastpage

5

Abstract

This paper aims to develop an efficient content - based image retrieval approach for brain image database. The combination of Cohen-Daubechies-Feauveau (CDF) 9/7 wavelet and Local Ternary Co-occurrence Patterns (LTCoP) is used for feature extraction in solving the brain image retrieval problem. The experimental dataset used for the retrievalpurpose is from OASIS - MRI database. The mean precision rate is calculated for performance evaluation. The effectiveness of our approach is analyzed by comparing its performance with Gabor transform based local ternary co-occurrence pattern. The result shows that our approach is comparatively better than the existing method.

Keywords

biomedical MRI; brain; feature extraction; image retrieval; medical image processing; wavelet transforms; Cohen-Daubechies-Feauveau 9-7 wavelet; Gabor transform based local ternary cooccurrence pattern; OASIS-MRI database; brain image database; brain image retrieval; feature extraction; Biomedical imaging; Biomedical measurement; Face; Histograms; Wavelet transforms; Feature extraction; Gabor transforms; Histogram; Local Ternary Co-occurrence Pattern; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics and Communication Systems (ICECS), 2014 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-2321-2

Type

conf

DOI

10.1109/ECS.2014.6892540

Filename

6892540