System and method to manipulate an image

• US 20090022429A1
• Filed: 05/02/2008
• Published: 01/22/2009
• Est. Priority Date: 05/03/2007
• Status: Active Grant

• Current Assignee: Hand Held Products Incorporated (Honeywell International Inc.)
• Original Assignee: Andrew Longacre Jr, Matthew Pankow, Thomas Hawley
• Inventors: Hawley, Thomas, Pankow, Matthew, Longacre, Andrew JR.
• Granted Patent: US 8,630,491 B2
• Time in Patent Office: Days
• US Class Current: 382/313
• CPC Class Codes: G06K 7/1443 locating of the code in an image
• CPC Class Codes: G06K 7/1447 extracting optical codes from image or text carrying said optical code
• CPC Class Codes: G06K 7/1452 detecting bar code edges
• CPC Class Codes: G06K 7/1456 determining the orientation of the optical code with respect to the reader and correcting therefore
• CPC Class Codes: G06K 7/146 the method including quality enhancement steps
• CPC Class Codes: G06V 10/242 by image rotation, e.g. by 90 degrees
• CPC Class Codes: G06V 10/243 by compensating for image skew or non-uniform image deformations
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 30/142 using hand-held instruments; Constructional details of the instruments
• CPC Class Codes: H04N 1/40068 Modification of image resolution, i.e. determining the values of picture elements at new relative positions H04N1/3935 takes precedence

Abstract

A method of operating an image reader comprising the steps of: capturing an image; recognizing a form within the captured image; and, cropping the captured image to the size of the form.

Claims

1. A method of operating an image reader comprising the steps of:

searching a digital image for nominally straight edges;

characterizing the nominally straight edges in terms of length and/or direction;

determining a predominant orientation of the nominally straight edges;

establishing a group of edges as a function of their proximity to the center of the image;

establishing a group of edges as a function of their proximity to other remaining edge positions; and

,

transmuting a rectangle bounding those edges into a rectified image.

2. A method in accordance with claim 1, wherein searching comprises searching an image in high resolution and low resolution.

3. A method in accordance with claim 1, further comprising the step of discarding edges not nominally parallel or perpendicular to the predominate orientation.

4. A method in accordance with claim 1, wherein the transmuting step comprises at least one of the following:

image cropping and image rotation.

5. A method in accordance with claim 1, wherein the steps occur automatically after an image is captured.

6. A method in accordance with claim 1, wherein searching comprises searching an image in high resolution and low resolution derived from a single image capture viewed both at high resolution and at lower resolution.

7. A method in accordance with claim 1, wherein some edges appear in both high and low resolution images.

25. A method in accordance with claim 1, wherein determining a predominant orientation of the nominally straight edges utilizes a histogram.

8. A method of operating an image reader comprising the steps of:

searching a digital image at a high resolution for nominally straight edges;

searching the digital image at a low resolution for nominally straight edges;

characterizing the nominally straight edges in terms of length and direction;

determining a predominant orientation of the nominally straight edges;

discarding edges not nominally parallel or perpendicular to the predominate orientation;

establishing a group of edges as a function of their proximity to the center of the image;

establishing a group of edges as a function of their proximity to other remaining edge positions; and

,

transmuting a rectangle bounding those edges into a rectified image.

9. A method in accordance with claim 8, wherein the transmuting step comprises at least one of the following:

image cropping and image rotation.

10. A method in accordance with claim 8, wherein the steps occur automatically after an image is captured.

11. A method in accordance with claim 8, wherein searching comprises searching an image in high resolution and low resolution derived from a single image capture viewed both at high resolution and at lower resolution.

12. A method in accordance with claim 8, wherein some edges appear in both high and low resolution images.

26. A method in accordance with claim 8, wherein determining a predominant orientation of the nominally straight edges utilizes a histogram.

13. An image reader comprising:

an image sensor for converting light into output signals representative of an image in a field of view (FOV) of the image sensor;

an illumination source for illuminating the field of view;

receive optics for directing light to the image sensor; and

a processor for;

searching an image for nominally straight edges;

characterizing the nominally straight edges in terms of length and/or direction;

determining a predominant orientation of the nominally straight edges;

establishing a group of edges as a function of their proximity to the center of the image;

establishing a group of edges as a function of their proximity to other remaining edge positions; and

,

transmuting a rectangle bounding those edges into a rectified image.

14. An image reader in accordance with claim 13, wherein searching comprises searching an image in high resolution and low resolution.

15. An image reader in accordance with claim 13, further comprising the step of discarding edges not nominally parallel or perpendicular to the predominate orientation.

16. An image reader in accordance with claim 13, wherein the transmuting step comprises at least one of the following:

image cropping and image rotation.

17. An image reader in accordance with claim 13, wherein the steps occur automatically after an image is captured.

18. An image reader in accordance with claim 13, wherein searching comprises searching an image in high resolution and low resolution derived from a single image capture viewed both at high resolution and at lower resolution.

19. An image reader in accordance with claim 13, wherein some edges appear in both high and low resolution images.

27. An image reader in accordance with claim 13, wherein determining a predominant orientation of the nominally straight edges utilizes a histogram.

20. An image reader comprising:

an image sensor for converting light into output signals representative of an image in a field of view (FOV) of the image sensor;

an illumination source for illuminating the field of view;

receive optics for directing light to the image sensor; and

a processor for;

searching a digital image at a high resolution for nominally straight edges;

searching the digital image at a low resolution for nominally straight edges;

characterizing the nominally straight edges in terms of length and direction;

determining a predominant orientation of the nominally straight edges;

discarding edges not nominally parallel or perpendicular to the predominate orientation;

establishing a group of edges as a function of their proximity to the center of the image;

establishing a group of edges as a function of their proximity to other remaining edge positions; and

,

transmuting a rectangle bounding those edges into a rectified image.

21. An image reader in accordance with claim 20, wherein the transmuting step comprises at least one of the following:

image cropping and image rotation.

22. An image reader in accordance with claim 20, wherein the steps occur automatically after an image is captured.

23. An image reader in accordance with claim 20, wherein searching comprises searching an image in high resolution and low resolution derived from a single image capture viewed both at high resolution and at lower resolution.

24. An image reader in accordance with claim 20, wherein some edges appear in both high and low resolution images.

28. An image reader in accordance with claim 20, wherein determining a predominant orientation of the nominally straight edges utilizes a histogram.