Texture Classification with Feature Analysis Using Wavelet Approach: A Review

Mayur Rajendra Sonawane, Dhiraj G. Agrawal

Abstract: Textures play important roles in many image processing applications, since images of real objects often do not exhibit regions of uniform and smooth intensities, but variations of intensities with certain repeated structures or patterns, referred to as visual texture. The textural patterns or structures mainly result from the physical surface properties, such as roughness or oriented structured of a tactile quality. It is widely recognized that a visual texture, which can easily perceive, is very difficult to define. The difficulty results mainly from the fact that different people can define textures in applications dependent ways or with different perceptual motivations, and they are not generally agreed upon single definition of texture. The development in multi-resolution analysis such as Local Binary Pattern and wavelet transform help to overcome this difficulty.

Keywords: Wavelet Transform, Fourier transform, Fast Fourier transformation, Gray level co occurrence matrix, Feature Extraction

How to Cite?: Mayur Rajendra Sonawane, Dhiraj G. Agrawal, "Texture Classification with Feature Analysis Using Wavelet Approach: A Review", Volume 4 Issue 5, May 2015, International Journal of Science and Research (IJSR), Pages: 726-730, https://www.ijsr.net/getabstract.php?paperid=SUB154186, DOI: https://dx.doi.org/10.21275/SUB154186