What is it about?
Image segmentation is an important step in any image analysis process. It is a low level processing that precedes the measurement, comprehension and decision stage. The paper proposes a supervised classification algorithms based on information fusion combining three types of features extraction techniques ( statistical features taken out of GLCM matrices and structural features obtained using Gabor filters and the wavelet transform coefficients) . The obtained results leads to higher classification precision compared to applying a single classifier on textured images.
Featured Image
Read the Original
This page is a summary of: Classification of Textured Images Based on New Information Fusion Methods, IET Image Processing, May 2019, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-ipr.2018.6256.
You can read the full text:
Contributors
The following have contributed to this page
