An Improved Structural Technique for Automated Recognition of Handwritten Inform

Cover An Improved Structural Technique for Automated Recognition of Handwritten Inform
An Improved Structural Technique for Automated Recognition of Handwritten Inform
Patrick S P Patrick Shen Pei Wang
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# — > S 7. # — > S 8. SI — > S 9. S — > a Example 6. 3.
We can use UAG above to get the parsing sequence for English letter E: 31 a a a a a a as follows.
4 8 9 4 8 9 8 # S ==> S SI ==> S S ==> S a ==> S SI a ====> S a a ==> SI a a S 89 6 890 9 8 ====> a a a ==> a a a ====> a a a ====> a a a ====> a a a S SI a a a S SIS Sla S a 6 86898689 80898089 ====> a a a ========> a a a =========> a a a a a a a a a a a a SI a a SI a a a In the above example, we used UAG parsing sequence to represent a patte
...rn, but these sequences are rather long because some nonterminal to nonterminal parsing and terminal rules were involved. Now, we propose an algorithm, PATSEQ, which produces an unique shorter parsing sequence from a pattern. In order to describe this algorithm, some definitions are required.
Definition 6. 1. The neighbors of a pixel, pO, are identified by the eight directors, pi, p2, ... , p8 shown in Figure 6. 2.
32 pB p6 p7 p4 pO p8 p3 p2 pi Figure 6. 2. Pixel pO and its neighbors Definition 6.


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