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

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.