System and method for estimating the height of an object using tomosynthesis-like techniques

• US 8,508,591 B2
• Filed: 02/05/2010
• Issued: 08/13/2013
• Est. Priority Date: 02/05/2010
• Status: Active Grant

• Current Assignee: Applied Vision Corporation (Antares Vision S.p.A.)
• Original Assignee: Applied Vision Corporation (Antares Vision S.p.A.)
• Inventors: Sones, Richard A., Sebeny, Carl E.
• Primary Examiner(s): TORRENTE, RICHARD T
• Application Number:
  US12/700,764
• Publication Number:
  US 20110193953A1
• Time in Patent Office: 1,285 Days
• Field of Search: 348/135
• US Class Current: 348/135
• CPC Class Codes: G06T 2207/10112 Digital tomosynthesis [DTS]
• CPC Class Codes: G06T 2207/30108 Industrial image inspection
• CPC Class Codes: G06T 2207/30141 Printed circuit board [PCB]
• CPC Class Codes: G06T 7/571 from focus
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

Systems and methods to estimate the height profile of an object using tomosynthesis-like techniques. A plurality of raw images of an object to be characterized are acquired, where the plurality of raw images are representative of a plurality of spatial shifts of an imaging device relative to the object to be characterized. The raw images are processed to generate composite images, where each composite image corresponds to a unique image shift between spatially adjacent raw images. A volatility parameter value is calculated within a neighborhood of a same image pixel location for each composite image. The composite image having the largest volatility parameter value for the image pixel location is determined. A unique image shift, corresponding to the composite image having the largest volatility parameter value, is transformed into a height value representative of a height dimension of the image pixel location.

Claims

1. A method to estimate the height profile of an object, said method comprising:

acquiring a plurality of raw images of an object to be characterized using at least one imaging device, where said plurality of raw images are representative of a plurality of spatial shifts between said at least one imaging device and said object to be characterized occurring parallel to a surface that the object to be characterized is resting upon;

processing said plurality of raw images to generate a plurality of composite images, where each composite image of said plurality of composite images corresponds to a unique image shift between spatially adjacent raw images and is made up of a plurality of image pixel locations;

calculating a volatility parameter value within a neighborhood of at least one same image pixel location of said plurality of image pixel locations for each of said plurality of composite images;

determining which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location;

transforming said unique image shift, corresponding to said composite image having said largest volatility parameter value, into a height value representative of a height dimension of said at least one same image pixel location;

generating a height value for each image pixel location of said plurality of image pixel locations to form a height profile image of said object to be characterized; and

comparing said height profile image to at least one reference image to find any defects in said object to be characterized.

2. The method of claim 1 further comprising spatially translating said at least one imaging device relative to said object to be characterized during acquisition of said plurality of raw images.

3. The method of claim 1 further comprising spatially translating said object to be characterized relative to said at least one imaging device during acquisition of said plurality of raw images.

4. The method of claim 1 further comprising displaying said height profile image.

5. The method of claim 1 further comprising filtering said volatility parameter value across said plurality of composite images for said at least one same image pixel location before determining which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location.

6. The method of claim 1 wherein said unique image shift is a fraction of a distance between two adjacent image pixel locations.

7. The method of claim 1 wherein said processing said plurality of raw images includes using a sub-pixel location interpolation technique to generate said plurality of composite images.

8. A system to estimate the height profile of an object, said system comprising:

means for acquiring a plurality of raw images of an object to be characterized, where said plurality of raw images are representative of a plurality of spatial shifts between said means for acquiring and said object to be characterized occurring parallel to a surface that the object to be characterized is resting upon;

means for processing said plurality of raw images to generate a plurality of composite images, where each composite image of said plurality of composite images corresponds to a unique image shift between spatially adjacent raw images and is made up of a plurality of image pixel locations;

means for calculating a volatility parameter value within a neighborhood of at least one same image pixel location of said plurality of image pixel locations for each of said plurality of composite images;

means for determining which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location;

means for transforming said unique image shift, corresponding to said composite image having said largest volatility parameter value, into a height value representative of a height dimension of said at least one same image pixel location;

means for generating a height value for each image pixel location of said plurality of image pixel locations to form a height profile image of said object to be characterized; and

means for comparing said height profile image to at least one reference image to find any defects in said object to be characterized.

9. The system of claim 8 further comprising means for spatially translating said means for acquiring relative to said object to be characterized during acquisition of said plurality of raw images.

10. The system of claim 8 further comprising means for spatially translating said object to be characterized relative to said means for acquiring during acquisition of said plurality of raw images.

11. The system of claim 8 further comprising means for displaying said height profile image.

12. The system of claim 8 further comprising means for filtering said volatility parameter across said plurality of composite images for said at least one same image pixel location before determining which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location.

13. An apparatus to estimate the height profile of an object, said apparatus comprising:

at least one imaging device configured to acquire a plurality of raw images of an object to be characterized, where said plurality of raw images are representative of a plurality of spatial shifts between said at least one imaging device and said object to be characterized occurring parallel to a surface that the object to be characterized is resting upon; and

a vision engine operatively connected to said at least one imaging device and configured to;

process said plurality of raw images to generate a plurality of composite images, where each composite image of said plurality of composite images corresponds to a unique image shift between spatially adjacent raw images and is made up of a plurality of image pixel locations;

calculate a volatility parameter value within a neighborhood of at least one same image pixel location of said plurality of image pixel locations for each of said plurality of composite images,

determine which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location,

transform said unique image shift, corresponding to said composite image having said largest volatility parameter value, into a height value representative of a height dimension of said at least one same image pixel location,

generate a height value for each image pixel location of said plurality of image pixel locations to form a height profile image of said object to be characterized, and

compare said height profile image to at least one reference image to find any defects in said object to be characterized.

14. The system of claim 13 further comprising a spatial translation mechanism operatively connected to said at least one imaging device and to said vision engine, and configured to spatially translate said at least one imaging device relative to said object to be characterized.

15. The system of claim 13 further comprising a spatial translation mechanism configured to spatially translate said object to be characterized relative to said at least one imaging device.

16. The system of claim 13 further comprising a display operatively connected to said vision engine and configured to display said height profile image.

17. The system of claim 13 wherein said vision engine is further configured to filter said volatility parameter value across said plurality of composite images for said at least one same image pixel location before determining which composite image of said plurality of composite images has a largest volatility parameter value for said at least one same image pixel location.