Textures are one of the most important features in computer vision for many applications. Texture Feature Extraction is a method of capturing visual content of images for indexing & retrieval. General features such as extraction of color, texture and shape or domain specific features. GLCM to extract statistical texture features such as Contrast, Correlation, Energy, Entropy and Homogeneity. GLRLM to extract run length features such as SRE, LRE, GLN, RLN, LGRE and HGRE. Constructing combinations of the various extraction methods (GLCM & GLRLM) to get the data with sufficient accuracy. The experimental results demonstrated that texture feature extraction based on the KNN technique achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved and that it requires less computation time efficiently used for real time Object Tracking Applications.