Image processing apparatus, image processing method, image processing program, printed matter inspection apparatus, printed matter inspection method and printed matter inspection program

• US 20040146202A1
• Filed: 11/12/2003
• Published: 07/29/2004
• Est. Priority Date: 12/20/2002
• Status: Active Grant

• Current Assignee: Fuji Xerox Company Limited (Xerox Holdings Corp.)
• Original Assignee: Fuji Xerox Company Limited (Xerox Holdings Corp.)
• Inventors: Hyoki, Kenji
• Granted Patent: US 7,684,625 B2
• Time in Patent Office: Days
• US Class Current: 382/209
• CPC Class Codes: G06T 2207/30144 Printing quality
• CPC Class Codes: G06T 3/02 Affine transformations for image registration G06T3/147; for image mosaicing G06T3/4038
• CPC Class Codes: G06T 5/80 Geometric correction
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration

Abstract

A split image generation portion generates split images. A split projected waveform generation portion generates split projected waveforms from the split images respectively. A projected waveform synthesizer portion generates projected waveforms by combining the split projected waveforms. A feature volume extraction portion extracts feature volumes from the generated projected waveforms. A feature volume correlation portion correlates feature volume data of a target image with feature volume data of a reference image. A correction value calculation portion calculates correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of the correlation and generates an n-dimensional lookup table. An image collation portion collates the target image with the reference image in consideration of the geometrical distortion by using the lookup table.

Claims

1. An image processing apparatus for collating a target image as a subject of inspection with a reference image, comprising:

a projected waveform generation unit for generating a projected waveform of the reference image and a projected waveform of the target image;

a feature volume extraction unit for extracting feature volumes from the projected waveforms and generating feature volume data respectively;

a feature volume correlation unit for correlating the feature volume data of the target image with the feature volume data of the reference image;

a correction value calculation unit for calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

a collation unit for collating the target image with the reference image by using the correction values.

2. An image processing apparatus according to claim 1, wherein:

the correction value calculation unit generates an n-dimensional lookup table on which the correction values are held as data and which is used for correcting the geometrical distortion; and

the collation unit uses the n-dimensional lookup table for performing collation.

3. An image processing apparatus according to claim 1, wherein:

the correction value calculation unit generates an n-dimensional lookup table on which the correction values and data interpolated between the correction values are held and which is used for correcting the geometrical distortion; and

the collation unit uses the n-dimensional lookup table for performing collation.

4. An image processing apparatus according to claim 1, wherein

the feature volume correlation unit correlates the feature volume data with each other by using DP matching.

5. An image processing apparatus according to claim 1, wherein

the feature volume correlation unit correlates respective elements of the feature volume data with each other successively.

6. An image processing apparatus according to claim 1, wherein

the projected waveform generation unit includes:

a split image generation unit for generating split images by splitting each image into m×

n blocks;

a split projected waveform generation unit for generating projected waveforms from the split images; and

a projected waveform synthesizer unit for generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively.

7. An image processing apparatus comprising:

a split image generation unit for generating split images by splitting each image into m×

n blocks;

a split projected waveform generation unit for generating projected waveforms from the split images; and

a projected waveform synthesizer unit for generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively.

8. An image processing apparatus for collating a target image as a subject of inspection with a reference image, comprising:

an n-dimensional lookup table used for correcting geometrical distortion in accordance with coordinates; and

a collation unit for collating the target image with the reference image by using the n-dimensional lookup table.

9. An image processing method for collating a target image as a subject of inspection with a reference image, comprising:

generating a projected waveform of the reference image and a projected waveform of the target image;

extracting feature volumes from the projected waveforms and generating feature volume data respectively;

correlating the feature volume data of the target image with the feature volume data of the reference image;

calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

collating the target image with the reference image by using the correction values.

10. An image processing method according to claim 9, wherein:

an n-dimensional lookup table on which the correction values are held as data and which is used for correcting the geometrical distortion is generated; and

the n-dimensional lookup table is used when the target image is collated with the reference image.

11. An image processing method according to claim 9, wherein:

an n-dimensional lookup table on which the correction values and data interpolated between the correction values are held and which is used for correcting the geometrical distortion is generated; and

the n-dimensional lookup table is used when the target image is collated with the reference image.

12. An image processing method according to claim 9, wherein

DP matching is used for correlating the feature volume data with each other.

13. An image processing method according to claim 9, wherein

elements of the feature volume data are collated with each other successively to thereby perform correlation of the feature volume data with each other.

14. An image processing method according to claim 9, wherein

the generating of the projected waveforms includes:

generating split images by splitting an image into m×

n blocks;

generating projected waveforms from the split images; and

generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively.

15. An image processing method comprising:

generating split images by splitting each image into m×

n blocks;

generating projected waveforms from the split images; and

generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively.

16. An image processing method for collating a target image as a subject of inspection with a reference image, comprising:

generating an n-dimensional lookup table used for correcting geometrical distortion in accordance with coordinates; and

collating the target image with the reference image by using the n-dimensional lookup table.

17. An image processing program executed by a computer for collating a target image as a subject of inspection with a reference image, comprising:

generating a projected waveform of the reference image and a projected waveform of the target image;

extracting feature volumes from the projected waveforms and generating feature volume data respectively;

correlating the feature volume data of the target image with the feature volume data of the reference image;

calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

collating the target image with the reference image by using the correction values.

18. An image processing program according to claim 17, wherein:

the calculating of the correction values generates an n-dimensional lookup table on which the correction values are held as data and which is used for correcting the geometrical distortion; and

the collating of the target image with the reference image uses the n-dimensional lookup table for performing collation.

19. An image processing program according to claim 17, wherein:

the calculating of the correction values generates an n-dimensional lookup table on which the correction values and data interpolated between the correction values are held and which is used for correcting the geometrical distortion; and

the collating of the target image with the reference uses the n-dimensional lookup table for performing collation.

20. An image processing program according to claim 17, wherein

the correlating of the feature volume data correlates the feature volume data with each other by using DP matching.

21. An image processing program according to claim 17, wherein

the correlating of the feature volume data correlates respective elements of the feature volume data with each other successively.

22. An image processing program according to claim 17, wherein

the generating of the projected waveform includes:

generating split images by splitting each image into m×

n blocks;

generating projected waveforms from the split images; and

generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively, so that the generating of the projected waveform generates the projected waveform of the reference image and the projected waveform of the target image respectively.

23. An image processing program executed by a computer, comprising:

generating split images by splitting each image into m×

n blocks;

generating projected waveforms from the split images; and

generating a projected waveform of the whole image or a partial image larger in area than one split image by combining the projected waveforms generated from the split images respectively.

24. An image processing program executed by a computer for collating a target image as a subject of inspection with a reference image, comprising:

an n-dimensional lookup table used for correcting geometrical distortion in accordance with coordinates; and

collating the target image with the reference image by using the n-dimensional lookup table.

25. A printed matter inspection apparatus for inspecting printed matter, comprising:

a reference image storage unit for storing a reference image used for forming the printed matter;

an image reader unit for reading an image of the printed matter as a target image which is a subject of inspection;

a projected waveform generation unit for generating a projected waveform of the reference image and a projected waveform of the target image;

a feature volume extraction unit for extracting feature volumes from the projected waveforms and generating feature volume data respectively;

a feature volume correlation unit for correlating the feature volume data of the target image with the feature volume data of the reference image;

a correction value calculation unit for calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

a collation unit for collating the target image with the reference image by using the correction values.

26. A printed matter inspection method for inspecting printed matter, comprising:

reading an image of the printed matter as a target image which is a subject of inspection;

generating a projected waveform of a reference image and a projected waveform of the target image;

extracting feature volumes from the projected waveforms and generating feature volume data respectively;

correlating the feature volume data of the target image with the feature volume data of the reference image;

calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

collating the target image with the reference image by using the correction values.

27. A printed matter inspection program executed by a computer for inspecting printed matter, comprising:

reading an image of the printed matter as a target image which is a subject of inspection;

storing an image used for forming the printed matter as a reference image;

generating a projected waveform of the reference image and a projected waveform of the target image;

extracting feature volumes from the projected waveforms and generating feature volume data respectively;

correlating the feature volume data of the target image with the feature volume data of the reference image;

calculating correction values in accordance with geometrical distortion between the reference image and the target image on the basis of a result of correlation of the feature volume data; and

collating the target image with the reference image by using the correction values.