An Improved Color Image Representation Method by Using Direct Non-symmetry and Anti-packing Model with Triangles and Rectangles

Image representation is an important issue in computer graphics, computer vision, robotics, image processing and pattern recognition. In this paper, we proposed an improved color image representation method by using the direct non-symmetry and anti-packing model with triangles and rectangles (DNAMTR). Also, we propose an algorithm of the DNAMTR for color images and analyze the total data amount of the algorithm. By comparing the representation algorithm of the DNAMTR with those of the latest direct non-symmetry and anti-packing model (DNAM) and the popular linear quadtree, the experimental results presented in this paper show that the former can greatly reduce the numbers of subpatterns or nodes and simultaneously save the data storage much more effectively than the latter.

[1]  Yun-Ping Zheng A Color Image Representation Method Based on Non-Symmetry and Anti-Packing Model , 2007 .

[2]  Allen Klinger,et al.  Data Structures and Pattern Recognition , 1978 .

[3]  Eero P. Simoncelli,et al.  Nonlinear image representation for efficient perceptual coding , 2006, IEEE Transactions on Image Processing.

[4]  Michael J. Laszlo,et al.  A genetic algorithm using hyper-quadtrees for low-dimensional k-means clustering , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Yunping Zheng,et al.  A Direct Non-Symmetry and Anti-Packing Model for Color Images , 2008, 2008 Fourth International Conference on Natural Computation.

[6]  Michael J. Laszlo,et al.  A Genetic Algorithm Using Hyper-Quadtrees , 2006 .

[7]  C-L Wang,et al.  Quadtree and statistical model-based lossless binary image compression method , 2005 .

[8]  Yunping Zheng,et al.  A Novel Algorithm for Triangle Non-symmetry and Anti-packing Pattern Representation Model of Gray Images , 2007, ICIC.

[9]  Mourad Zribi,et al.  Unsupervised Bayesian image segmentation using orthogonal series , 2007, J. Vis. Commun. Image Represent..

[10]  Zhihai He Peak Transform for Efficient Image Representation and Coding , 2007, IEEE Transactions on Image Processing.

[11]  Yanmin He,et al.  Fast $M$ -Term Pursuit for Sparse Image Representation , 2008, IEEE Signal Processing Letters.

[12]  Hai Tao,et al.  Representing Images Using Nonorthogonal Haar-Like Bases , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Irene Gargantini,et al.  An effective way to represent quadtrees , 1982, CACM.