Texture Classification Using Uniform Extended Local Ternary Patterns

We present an extension to the well-known local binary pattern (LBP) feature descriptor. The newly defined descriptor known as extended local ternary pattern (ELTP) exhibits better noise resistivity than the original LBP, while maintaining computational simplicity. We further investigate the presence of uniform patterns in ELTP. With a slight modification in the definition of uniformity, it is found experimentally that uniform ELTP account for 80% of all patterns in texture images. Comparative performance analysis indicates that the proposed uniform ELTP is more effective than uniform LBP for texture classification tasks.