Texture Classification based on Texton Patterns using on various Grey to Greylevel Preprocessing Methods

Textural patterns can often be used to recognize familiar objects in an image or retrieve images with similar texture from a database. Texture patterns can provide significant and abundance of texture and shape information. One of the recent significant and important texture features called Texton represents the various patterns of image which is useful in texture analysis. However sometimes the textured image obtained may not be of good quality and this may lead to improper detection of significant patterns. To enhance the quality or better illumination or contrast or sharpening effect, the present paper applied various local grey to grey level preprocessing steps on textured data. Grey to grey level preprocessing is required because the patterns on textons can be evaluated only on grey level textures. The present paper evaluated the occurrence behavior of various texton patterns based on the various grey to grey level pre processing methods, for an efficient rotationally invariant texture classification. The experimental results on various stone textures indicate the efficacy of the proposed method when compared to other methods.