An Improved Binary Image Representation Method by Using Non-symmetry and Anti-packing Model with Triangles and Squares

Author(s):  
Yunping Zheng ◽  
Xi Guo
2011 ◽  
Vol 143-144 ◽  
pp. 755-759
Author(s):  
Jie He ◽  
Yun Ping Zheng ◽  
Hui Guo

The Non-symmetry and Anti-packing Model (NAM) is an effective pattern representation model. In this paper, a new NAM image representation method by using the nonoverlapping square subpatterns, which is called the square NAM (SNAM) representation, is proposed. The idea of the SNAM representation is described. The square subpattern has its own significant characteristics when it is compared with other subpatterns such as the triangle and the rectangle, etc. Unlike the general triangle subpattern which needs to record three vertices of the triangle and unlike the rectangle subpattern which needs to record the coordinates of its starting point, length and width, the square subpattern needs to record only its starting point and the side. Therefore, as far as a single record of the square subpattern is concerned, it can save storage space more effectively. The theoretical and experimental results presented in this paper prove the efficiency and the effectiveness of the proposed SNAM representation method for binary images.


2011 ◽  
Vol 143-144 ◽  
pp. 746-749
Author(s):  
Yun Ping Zheng ◽  
Zu Jia Li ◽  
Mudar Sarem ◽  
Qing Hong Yang ◽  
Xiu Xiu Liao

In this paper, by controlling the ratio of the length and the width of a homogenous block, we proposed an improved algorithm for the gray image representation by using the Rectangular Non-symmetry and Anti-packing Model Coding (RNAMC) and extended shading approach, which is called the IRNAMC image representation method. Also, we present an IRNAMC representation algorithm of gray images. By comparing our proposed IRNAMC method with the conventional S-Tree Coding (STC) method, the experimental results presented in this paper show that the former can significantly reduce the lower bit rate and the number of homogenous blocks than the latter whereas remaining the satisfactory image quality. Also, the experimental results show that by controlling the ratio of the length and the width, we can improve the reconstructed image quality of the RNAMC method.


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