The choice of the superior wavelet bases in the image texture identifies;

Develops a system that can analyzes MRI medical image texture feature,the functions of which include implementing image display,reading image information,selecting ROI,extracting five texture features and forming samples that is saved to the samples library,as well as classifying the samples using four different methods and statistical tests for the various features.

Combing the energy,coarseness and structure property of the texture,an algorithm for image texture feature detection based on Gabor filter is proposed according to human vision characteristics.

Mapping based complex contourlet transform texture image retrieval system

Second generation contourlet transform based texture image retrieval system

Research on texture image segmentation method

Leather has typical texture and the texture images differ from common gray images in pixels space dist.

In this paper an approach to object extraction in textured images is proposed based on a mask stochastic method in object edge extraction, and its aim is to detect the object hidden in texture.

In the field of textured image segmentation,some propose a two step textured image segmentation method by taking interacting parameter of neighbor pixel in Gauss Markov Random Field as features,taking Gauss Mixture Model as classifier.

The author proposes a textured image segmentation algorithm which is based on multiresolution wavelet and Gaussian mixture models.