A Statistical Identification Model (SIM) For Textural Images

The extraction of Textural Images Properties and its Identification relative to one of textural Images groups was and still the main concern for many researchers and studies in many application fields that because of the wide applicability for such kind of studies on many applications. This research came for building a application model to determine Identification textural pieces to belong to one of proposed textural groups or not belong to any textural Images in the Experiment based on statistical model parameters for determine the range of convergence or divergence for each texture thoughtful, also research included percentages to the range of determining to belong to random piece textural to one of the textural images of the study. Discrimination process depend on the parameters of the proposed model. Experimental data representation as (24) textural images divided into (3) main groups. Experimental results showing the ability of textural features for identify and discriminate of textural part to belong to main textural images with difference identification ratio depending on (textural kinds , textural features). The proposed model can be adopted for many images application such as (MRI, Remote Sensing).