GREY LEVEL CO-OCCURRENCE MATRICES : GENERALISATION AND SOME NEW FEATURES

International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012

[1]  Jacob D. Furst,et al.  CO-OCCURRENCE MATRICES FOR VOLUMETRIC DATA , 2004 .

[2]  Yu Nenghai,et al.  A set of novel textural features based on 3D co-occurrence matrix for content-based image retrieval , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[3]  Tieniu Tan,et al.  Brief review of invariant texture analysis methods , 2002, Pattern Recognit..

[4]  Yong Haur Tay,et al.  RECENT TRENDS IN TEXTURE CLASSIFICATION: A REVIEW , 2009 .

[5]  Maria Petrou,et al.  Multidimensional Co-occurrence Matrices for Object Recognition and Matching , 1996, CVGIP Graph. Model. Image Process..

[6]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .

[7]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[9]  R.M. Haralick,et al.  Statistical and structural approaches to texture , 1979, Proceedings of the IEEE.

[10]  K. Hammouche,et al.  Multidimensional Texture Analysis for Unsupervised Pattern Classification , 2008 .

[11]  J. Macgregor,et al.  Image texture analysis: methods and comparisons , 2004 .

[12]  Alaa Eleyan,et al.  Co-occurrence based statistical approach for face recognition , 2009, 2009 24th International Symposium on Computer and Information Sciences.