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Poster Session 4
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Digital Image Data Recovery from Printed Image
3. Experimental and result
The image Fig. 1(a) is obtain by scanning the printed image and store in the memory PC. Enlargement a part of Fig. 1(a) is shown in Fig.1(b). It is cleared that there exists some undesired texture in the scanned image. Hence, to reproduce a complete digital image, this kind of texture must be removed. Here, the Fourier transform is applied to the scanned image obtain its spectrum which is shown in Fig. 3. The undesired texture or periodic noise is easy found in high frequency portion of the spectrum. A filter function of Fig. 4, which defined certain bands for rejecting the specified frequencies of undesired texture, is applied to the image spectrum. The filtered spectrum is shown in Fig. 5. The resulting image shown in Fig.6 is achieved by Appling inverse Fourier transform to the spectrum of Fig. 5. The Fig. 6 shows the periodic noise free image.
Figure 3 Spectrum of image in Fig. 1(a) obtained by using transform
Figure 4 Specified filter function to remove the spectrum of undesired texture is high frequency portion
Figure 5 Filtered spectrum
Figure 6 Resultant of digital image data obtained by the inverse Fourier transform of filtered spectrum
4. Conclusion
This paper presents a method of image data recovery from printed image by using scanning device and PC. The scanned image is stored to be digital form. However, for some printing reason, the scanned image is consisted of undesired texture or periodic noise. This kind of noise effects a specified frequencies spectrum. Then, some filter function can be applied to remove the undesired texture. The result of digital data image is accomplished by applying the increase Fourier transform to the filtered spectrum. Hence, the digital image data can be recovered from the printed image.
5. Acknowledgement
The authors wish to thank the staff of Thailand Remote Sensing for providing monthly TRSC Newsletter.
6. Reference
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J.A Richards, "Remote Sensing Digital Image Analysis: Introduction," Springer-Verlag, Berlin, 1986.
- S.P. Banks, "Signal processing, Image Processing and Pattern Recognition," Prentice Hall. New York, 1990.
- J.C,Russ, " The Image Processing Handbook," 2nd Edition, IEEE Press, 1994.
- M.A. Sid-Ahmed, "Image Processing: Theory, Algorithm and Architectures," McGraw- Hill Books Co., 1995.
- P.M.Embree and B. Kimble, "C Language Algorithms for Digital Signal Processing," Prentice Hall, New York, 1991.
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