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Table 3 Comparison of the performance of the proposed and the other algorithms against DIBCO dataset

From: An innovative document image binarization approach driven by the non-local p-Laplacian

Dataset

Models

FM %

Fps %

PSNR

DRD

DIBCO 2009

Wang [10]

77.96

81.42

14.77

14.71

Jacobs et al. [11]

75.19

77.63

15.04

12.50

Jacobs et al. [12]

75.71

76.46

13.74

7.46

Rivest-Hénault et al. [15]

75.50

75.30

14.37

19.64

Guo et al. [14]

83.31

84.92

16.64

9.40

Proposed

88.34

93.03

17.41

4.98

DIBCO 2010

Wang [10]

77.63

86.13

16.26

5.60

Jacobs et al. [11]

49.65

54.84

14.35

9.75

Jacobs et al. [12].

67.62

68.78

14.66

8.02

Rivest-Hénault et al. [15]

69.97

76.41

15.37

7.45

Guo et al. [14]

86.75

89.74

17.93

3.62

Proposed

88.80

94.46

18.60

3.06

DIBCO 2011

Wang [10]

81.94

86.98

15.76

7.26

Jacobs et al. [11]

73.33

77.26

14.32

13.92

Jacobs et al. [12]

77.90

74.60

14.68

6.28

Rivest-Hénault et al. [15]

69.40

70.19

12.70

51.25

Guo et al. [14]

83.82

87.32

16.50

6.55

Proposed

88.63

94.55

17.56

3.55

DIBCO 2012

Wang [10]

78.22

83.34

16.25

7.35

Jacobs et al. [11]

65.31

69.20

15.28

8.83

Jacobs et al. [12]

81.57

81.45

16.26

5.98

Rivest-Hénault et al. [15]

73.59

76.53

15.29

12.37

Guo et al. [14]

86.40

89.00

17.86

4.67

Proposed

88.89

93.41

18.81

3.74

DIBCO 2013

Wang [10]

80.07

83.98

16.51

9.51

Jacobs et al. [11]

73.66

77.24

15.98

9.85

Jacobs et al. [12]

77.72

82.34

16.54

9.20

Rivest-Hénault et al. [15]

77.33

78.86

15.81

11.48

Guo et al. [14]

82.35

85.16

17.37

8.09

Proposed

89.62

94.75

19.21

3.11

DIBCO 2014

Wang [10]

79.93

84.78

16.31

6.34

Jacobs et al. [11]

65.43

73.70

14.15

9.24

Jacobs et al. [12]

74.23

81.29

15.41

7.44

Rivest-Hénault et al. [15]

81.20

85.82

17.00

5.58

Guo et al. [14]

92.30

94.86

19.17

2.37

Proposed

92.34

96.03

19.02

2.55

DIBCO 2016

Wang [10]

86.92

89.93

18.05

4.61

Jacobs et al. [11]

79.09

81.13

16.67

6.13

Jacobs et al. [12]

83.25

87.98

17.66

5.32

Rivest-Hénault et al. [15]

83.06

84.43

16.49

7.27

Guo et al. [14]

88.51

90.46

18.42

4.13

Proposed

90.22

93.82

18.94

3.60