Means for using microstructure of materials surface as a unique identifier

• US 9,390,345 B2
• Filed: 12/04/2015
• Issued: 07/12/2016
• Est. Priority Date: 09/05/2005
• Status: Active Grant

• Current Assignee: AlpVision S. A.
• Original Assignee: AlpVision S. A.
• Inventors: Di Venuto Dayer, Celine V, Kutter, Martin, Jordan, Frederic
• Primary Examiner(s): Liew, Alex
• Application Number:
  US14/959,803
• Publication Number:
  US 20160140420A1
• Time in Patent Office: 221 Days
• Field of Search: 382128-134, 382141-152, 382181-231
• US Class Current: 1/1
• CPC Class Codes: G04B 47/00 Time-pieces combined with other articles which do not interfere with the running or the time-keeping of the time-piece clockwork cases for special purposes G04B37/12; clocks with magnifying glass built in the face G04B39/00; time-pieces in which parts or cases produce special effects, e.g. aesthetic effects, G04B45/00, particularly with inscriptions or pictures moved by hand G04B45/003, with specially shaped cases or parts G04B45/0069; combination of writing or drawing implements with devices for indicating time B43K29/087; combined with cameras, projectors, or photographic printing apparatus G03B29/00
• CPC Class Codes: G06T 2207/30176 Document
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06V 10/242 by image rotation, e.g. by 90 degrees
• CPC Class Codes: G06V 10/7515 Shifting the patterns to accommodate for positional errors
• CPC Class Codes: G06V 20/66 Trinkets, e.g. shirt buttons or jewellery items recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/80 Recognising image objects characterised by unique random patterns
• CPC Class Codes: G06V 30/248 involving plural approaches, e.g. verification by template match; Resolving confusion among similar patterns, e.g. "O" versus "Q" G06V30/242 takes precedence
• CPC Class Codes: G06V 30/2504 Coarse or fine approaches, e.g. resolution of ambiguities or multiscale approaches
• CPC Class Codes: G06V 40/1371 Matching features related to minutiae or pores
• CPC Class Codes: G07D 7/2033 Matching unique patterns, i.e. patterns that are unique to each individual paper
• CPC Class Codes: G09C 1/00 Apparatus or methods whereby a given sequence of signs, e.g. an intelligible text, is transformed into an unintelligible sequence of signs by transposing the signs or groups of signs or by replacing them by others according to a predetermined system cryptographic typewriters G09C3/00
• CPC Class Codes: H04L 9/3278 using physically unclonable functions [PUF]
• CPC Class Codes: H04N 23/56 provided with illuminating means

Abstract

The present application concerns the visual identification of materials or documents for tracking or authentication purposes.

It describes methods to automatically authenticate an object by comparing some object images with reference images, the object images being characterized by the fact that visual elements used for comparison are non-disturbing for the naked eye. In some described approaches it provides the operator with visible features to locate the area to be imaged. It also proposes ways for real-time implementation enabling user friendly detection using mobile devices like smart phones.

Claims

1. A method to authenticate a product comprising a parameter settings phase, an acquisition phase and an identification phase;

the parameter setting phase comprising;

selecting an imaging lighting orientation, an imaging resolution and a region of interest on the reference product surface;

the acquisition phase comprising the steps of;

lighting, with an imaging device, the surface of a first reference product item with the imaging lighting orientation;

capturing, with the imaging device, an image of a microstructure of the region of interest on the reference product surface, wherein the image has sufficient resolution to show a least one product surface microstructure feature at the pixel level;

computing, with the imaging device, an image feature to characterize the captured image; and

storing, with the imaging device, the image feature in a database;

the identification phase comprising the steps of;

lighting, with an imaging device, the surface of a product to authenticate with the imaging lighting orientation;

capturing, with the imaging device, an image of a microstructure of the region of interest on the surface of the product to authenticate, wherein the image has sufficient resolution to show a least one microstructure feature at the pixel level;

computing, with the imaging device, an initial image feature to characterize the captured image of the region of interest on the surface of the product to authenticate;

querying, with the imaging device, for a reference product item, a reference image feature in the database;

comparing the initial image feature and the reference image feature, with an image matching technique;

responsive to the comparison, computing, with the imaging device, a refined image feature to characterize the captured image;

measuring a correlation metric between the refined image feature and the reference image feature; and

identifying a match between the product to authenticate and the reference product item when the correlation metric is above a predefined threshold.

2. The method of claim 1, wherein the image feature is a matrix of values corresponding to a color component sampled along a uniform orthogonal grid.

3. The method of claim 1, wherein the image feature is a 1D profile.

4. The method of claim 1, wherein the image feature is a compressed image.

5. The method of claim 1, wherein the image feature is a set of invariant features.

6. The method of claim 1, wherein the image feature is a set of Fourier coefficients.

7. The method of claim 1, wherein the image matching technique is cross-correlation.

8. The method of claim 1, wherein the image matching technique is applied in the transform domain.

9. The method of claim 1, wherein the image matching technique is applied in the spatial domain.

10. The method of claim 1, wherein the image matching technique is a contour matching technique.

11. The method of claim 1, wherein the image matching technique is a color matching technique.

12. The method of claim 1, wherein the image matching technique is a fingerprint minutiae matching technique.

13. The method of claim 1, wherein the refined image feature is compensated for translation.

14. The method of claim 1, wherein the refined image feature is compensated for rotation.

15. The method of claim 1, wherein the refined image feature is a flattened version of the captured image.

16. The method of claim 1, wherein the refined image feature is a combination of several cross-correlations.

17. The method of claim 1, wherein the refined image feature has a larger size than the initial image feature.

18. The method of claim 1, wherein the correlation metric is the Signal-to-Noise Ratio (SNR) of the cross-correlation between the refined image feature and the reference image feature.