Abstract

Hybrid image processing has been described for adaptive binarization by efficiently combining optical analog and digital image processing techniques. A defocused image obtained by an optical system served as the 2-D variable contrast threshold for adaptive binarization in the digital processing. Experimental results show that the method of hybrid image processing is effective for adaptive binarization for simplicity of data handling and economy of computer time.

© 1978 Optical Society of America

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References

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  1. H. C. Andrews, Appl. Opt. 15, 495 (1976).
    [CrossRef] [PubMed]
  2. A. Rosenfeld, in Picture Processing by Computer (Academic, New York, 1969), p. 88.
  3. Y. Ichioka, Proc. Soc. Photo-Opt. Instrum. Eng. 74, 140 (1976).

1976

Y. Ichioka, Proc. Soc. Photo-Opt. Instrum. Eng. 74, 140 (1976).

H. C. Andrews, Appl. Opt. 15, 495 (1976).
[CrossRef] [PubMed]

Andrews, H. C.

Ichioka, Y.

Y. Ichioka, Proc. Soc. Photo-Opt. Instrum. Eng. 74, 140 (1976).

Rosenfeld, A.

A. Rosenfeld, in Picture Processing by Computer (Academic, New York, 1969), p. 88.

Appl. Opt.

Proc. Soc. Photo-Opt. Instrum. Eng.

Y. Ichioka, Proc. Soc. Photo-Opt. Instrum. Eng. 74, 140 (1976).

Other

A. Rosenfeld, in Picture Processing by Computer (Academic, New York, 1969), p. 88.

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Figures (2)

Fig. 1
Fig. 1

Comparison of hard clipping and adaptive binarization: (a) original image; (b) image degraded by contamination (full line), constant threshold for hard clipping (dashed line), and variable contrast threshold for adaptive binarization (dotted line); (c) hard clipped image; and (d) processed image by adaptive binarization.

Fig. 2
Fig. 2

Experimental results of adaptive binarization using hybrid processing: (A) image to be processed; (B) hard clipped image; (C) defocused image of (A); (D) processed image by adaptive binarization; and (E) image with pepper and salt noise removed.

Equations (7)

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g ( x ) = ε 2 { 1 + sgn [ f ( x ) f ¯ ( x ) ] } ,
sgn ( u ) = 1 for u > 0 = 0 for u = 0 = 1 for u < 0 ,
ε = 1 for u 0 = 2 for u = 0.
f ¯ ( x ) = f ( x ) * h ( x ) ,
f ( x ) = s ( x ) + c ( x ) f ¯ ( x ) = s ¯ ( x ) + c ¯ ( x ) ,
f ( x ) = s ( x ) c ( x ) f ¯ ( x ) = s ¯ ( x ) c ¯ ( x ) ,
g ( x ) = ε 2 { 1 + sgn [ s ( x ) s ¯ ( x ) ] } = ε 2 ( 1 + sgn { s ( x ) * [ δ ( x ) h ( x ) ] } ) .

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