Texture feature extraction using 2-D Gabor Filters

Abstract

Texture feature extraction is a procedure of computing and describing the features and characteristics of image which numerically describes that texture image properties. This paper investigated texture feature extraction using 2-D Gabor Filter to extract the texture features of Inverse Fast Fourier Transform (IFFT), texture energy and transformed IFFT. The Gabor filter bank experimented on seventy two collected samples of skull-stripped T1-weighted, T2-weighted and FLAIR MRI brain images utilizing four frequencies and four orientations. Results showed that texture feature extractions of two highest frequencies with all four orientations produced the highest acceptance rate.