A Novel Approach of Texture Description using DWT and GLCM on Digital Images
Jitendra Jitendra, Triloki Pant · 2020 URSI Regional Conference on Radio Science ( URSI-RCRS) · 2020
Texture is a predominant characteristic in the images and very useful for identification of the objects. In the present work the focus is on the analysis of textural features in digital images. A dataset containing 8 images has been used in which the size of all images is 640×640 pixels. The Gray Level Co-occurrence Matrix (GLCM) with Discrete Wavelet Transform (DWT) is used to analyze the texture. Five textural measures, viz., contrast, correlation, energy, and entropy of scaled image are computed on four different offset values 00, 450, 900and 1350separately. It is observed that the value of entropy, correlation, energy and homogeneity decrease with the increasing levels of DWT whereas the value of contrast increases with corresponding offset value.