do local e global caracteristicas para identificacao de escrita

8/2/2019 do Local e Global Caracteristicas Para Identificacao de Escrita

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Figure 2 Application of a set of four gabor filters withrespective masks

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Figure 5 Window Positioning (a) Start of ink trace, (b)Choice of next side with exiting trace, (c) Initialposition of the next window, (d) Sliding the windowwith respect to trace

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Figure 6 Division of the word headlines (a) RegularDivision, (b) Sliding windows horizontally, (c)Following the ink trace

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1 2) 6 * ::5:: :@5:@ :5: :5:

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Figure 7 Clusters obtained on a document image

)* +) / )2/ (+$*422)D*12

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6/6

82%

84%

86%

88%

90%

92%

94%

96%

98%

Top1 Top2 Top3 Top4

Identification

Rate

Without Phase1,Text Division by Proposed method

With Phase1 (k=2),Text Division by Proposed Method

With Phase1 (k=2),Text Division by Earlier Method[13]

Figure 10 Comparison of Identification Rates

(

- ) + ** () * 2

* )2 (% 3) ()

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5/)*()22$*"$1

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1+(/$)/(+*2

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7:8 9% 0* 3% " % C V9 2**1(W/$=:@=B=;==%

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7@8 F% 0$ % )(4 % T+D$ V-* / / $ *W % * ) $ * (

9$1/$(K/)$@9/=@++%;@;:%

78 F% 0$ % )(4 V(/ F$+$

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78 %.T%K/$%0%C2/($** ))6*2G 1$ (/ (+% $ * (/9$1/>9A$(=+/B;=%

78 9(0TK/$C%K(+6%F%$Z$V- * /C( ETFW % * ) ;)[$* (9$1/>9=A06$+(=%

78 %FC%04V9*$$K/$)* **$ )2/ /W % * )

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7;8 %M%TV.$$F)?*-*W%*):)$ -4)+ E C2//0$E=%

7:8C%K%%3%M3\%%04V$*0C2/W/$%@@=++%:;:%

7::8% )(4 % 9 F% 0$ V9( -* / (+ K/0 E * ++ - +W KKK 3 * 9$1 F)$$/$=%++%B;B=%

7:=89% + M% T X-9) E$ (+X 2*) +% @ K/)) $-4)+ E C2/ />-EC[=A==%

7:@8% " M% T V- * C2 (W % * ) ;)[$* ( 9$1 />9=A06$+(=%

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