%0 Journal Article
%T A Brief Review on Texture Analysis Methods
%A Kuldeep Chaurasia
%A P. K. Garg
%J Studies in Surveying and Mapping Science
%D 2013
%I American Society of Science and Engineering
%X It is very difficult to identify an object just considering its color and shape. Texture is one of the important features which helps in identifying the objects that appear similar on the image but in reality they are different objects on the ground. It is commonly accepted that texture analysis plays a very significant role in object classification and outlining the important regions of a given gray level image. Image analysis process requires the knowledge of the characteristics of the pixels in an image. In this paper, five texture analysis methods namely; Structural, Statistical, Model based, Transform based and Soft computing have been described. Moreover, benefits and shortcoming of the different methods are also discussed.
%K Texture Analysis
%K Gray Level Co-Occurrence Matrix
%K Markov Random Field
%K Wavelet Transform
%K Fractals
%K Feature Extraction
%U http://www.as-se.org/ssms//Download.aspx?ID=3473