KR-20260066725-A - Generation of unique identifiers from a set of particles

Abstract

In a general embodiment, the unique marker comprises a plurality of particles. In some cases, the particles are distributed (e.g., fixed) on a surface, and a unique code can be generated based on the spatial characteristics (e.g., relative positions and relative orientations) of the projection of these particles onto a plane. A computing system can generate the unique code, and the spatial characteristics can be determined from data acquired by a camera or other type of optical detector.

Inventors

• 가톤 오피르
• 호지스 조나단
• 카라벨리 시넌

Assignees

• 더스트 아이덴티티, 아이엔씨.

Dates

Publication Date

20260512

Application Date

20240916

Priority Date

20230915

Claims (20)

1. In a method performed by a computing system, A step of acquiring one or more images of an object containing multiple particles; A step of identifying regions within one or more images corresponding to the plurality of particles; A step of determining the boundaries of the regions corresponding to the plurality of particles based on the above one or more images; A step of determining the geometric characteristics of the regions corresponding to the plurality of particles based on the above boundaries - the geometric characteristics of each region include a centroid and a principal axis -; A step of determining orientation information for pairs of regions within one or more images based on the above geometric characteristics - orientation information for each pair indicates the relative orientation of the principal axis of the first region with respect to the principal axis of the second region -; A step of determining positional information for pairs of regions within one or more images based on the geometric characteristics above—positional information for each pair represents the relative distance between the centroid of a first region and the centroid of a second region—; and A method comprising the step of generating an authentication code associated with the object based on the orientation information and the position information.
2. The method of claim 1, wherein the relative distance comprises a displacement along a first axis and a displacement along a second axis orthogonal to the first axis.
3. A method according to claim 1 or 2, wherein the orientation information comprises a rotation angle measured between the principal axis of the first region and the principal axis of the second region when the centroid of the first region and the centroid of the second region are aligned.
4. A method according to claim 1 or 2, wherein the geometric characteristics of each region comprise a transformation matrix for a reference coordinate system.
5. A method according to claim 1 or 2, wherein the authentication code comprises the position information and the orientation information.
6. A method according to claim 1 or 2, wherein the plurality of particles are a plurality of elongated particles.
7. A method according to claim 1 or 2, wherein the plurality of particles are a plurality of planar particles.
8. A method according to claim 7, wherein the surface normal vectors for the plurality of planar particles are parallel, and the orientation information represents the relative orientation with respect to a single plane.
9. In claim 7, the surface normal vectors for at least some of the plurality of planar particles are tilted with respect to the surface normal vector of the plane corresponding to the surface of the object and are not parallel; A method in which the geometric characteristics of regions corresponding to at least some of the plurality of planar particles are determined based on the projections of each planar particle onto a plane corresponding to the surface of the object.
10. In claim 7, the surface normal vectors for at least some of the plurality of planar particles are inclined with respect to the surface normal vector of the plane corresponding to the surface of the object and are not parallel; The above orientation information comprises relative orientations of surface normal vectors for at least some of the plurality of planar particles with respect to a surface normal vector of a plane corresponding to the surface of the object.
11. A method according to claim 1 or 2, wherein one or more regions corresponding to the plurality of particles are closed polygons having shape structures that may be concave or convex.
12. A method according to claim 11, wherein the authentication code is generated based on the parameterization of the shape structures.
13. A method according to claim 1 or 2, wherein the plurality of particles have non-uniform sizes.
14. A method according to claim 1 or 2, wherein the step of acquiring one or more images comprises the step of causing an image capture component communicating with the computing system to capture the one or more images.
15. A method according to claim 1 or 2, wherein the step of generating the authentication code includes the step of performing operations on the orientation information and the position information, wherein the operations include one or more of encoding, ranking, and filtering.
16. A method according to claim 1 or 2, wherein the plurality of particles are a plurality of elongated particles.
17. In computing systems, One or more processors; and It includes a computer-readable medium that stores instructions operable to perform operations when executed by one or more of the above-mentioned processors, and The above operations are: The operation of acquiring one or more images of an object containing multiple particles; An operation of identifying regions within one or more images corresponding to the plurality of particles; An operation of determining the boundaries of the regions corresponding to the plurality of particles based on the above one or more images; An operation to determine the geometric characteristics of the regions corresponding to the plurality of particles based on the above boundaries - the geometric characteristics of each region include a centroid and a principal axis - ; An operation to determine orientation information for pairs of regions within one or more images based on the above geometric characteristics—the orientation information for each pair represents the relative orientation of the principal axis of the first region with respect to the principal axis of the second region—; A step of determining positional information for pairs of regions within one or more images based on the geometric characteristics above—positional information for each pair represents the relative distance between the centroid of a first region and the centroid of a second region—; and A computing system comprising the step of generating an authentication code associated with the object based on the orientation information and the position information.
18. A computing system according to claim 17, wherein the relative distance includes a displacement along a first axis and a displacement along a second axis orthogonal to the first axis.
19. A computing system according to claim 17 or 18, wherein the orientation information includes a rotation angle measured between the principal axis of the first region and the principal axis of the second region when the centroid of the first region and the centroid of the second region are aligned.
20. A computing system according to claim 17 or 18, wherein the authentication code comprises the position information and the orientation information.

Description

Generation of unique identifiers from a set of particles Cross-reference of related applications This application claims priority to U.S. Provisional Application No. 63/582,993, filed September 15, 2023, titled “Generating Unique Identifiers from a Collection of Planar Bodies,” the entire contents of which are incorporated herein by reference. The following description concerns generating unique identifiers from a set of particles. Some products are manufactured with holograms, watermarks, fluorescent dyes, or other features that can be used as anti-counterfeiting measures. For example, such features can be used to verify the origin or authenticity of products. Such measures are important in many industries, including the food, pharmaceutical, electronics, luxury goods, and others. In some embodiments of what is described herein, techniques for generating one or more unique identifiers (also referred to herein as a unique code or authentication code) from one or more images of an object comprising a plurality of particles (e.g., planar particles, planar bodies, planar elements, or elongated particles) are disclosed. In a general embodiment, the unique marker may comprise particles placed on a surface. In some cases, the particles are placed on the surface of a target object, and the particles have well-defined relative positions and orientations on the surface. The particles may be physical parts of the unique marker that provide the basis for generating a unique identifier for the target object. Furthermore, deriving a two-dimensional representation of the particles can reduce the overall dimensionality of the group, allowing, for example, a camera or other imaging device to easily identify a unique set of relative positions and orientations within the unique marker. Thus, reduced dimensionality may allow the unique identifier to be easily determined from the unique marker without more sophisticated measuring devices. In some variations, the unique identifier may be determined using an imaging device, such as an optical imaging device (e.g., a camera, a stereographic camera, or a mobile phone) or other devices used for imaging (e.g., devices using X-rays or millimeter waves). FIG. 1 is a schematic diagram showing an exemplary group of particles that can be utilized in a unique marker for a target object. FIG. 2 is a schematic diagram that is a perspective view of an exemplary group of particles attached to the planar surface of a target object using a medium. FIG. 3 is a schematic diagram of an exemplary group of particles, each particle having an outer surface that defines a convex or concave polygonal shape. FIG. 4a is a schematic diagram, which is a plan view of an exemplary particle having a set of internal orthogonal axes including a major axis and a minor axis. FIG. 4b is a schematic diagram showing a plan view of exemplary particles of different sizes. FIG. 5 is a schematic diagram showing elevation views of two exemplary arrangements of objects and image planes that can be used to derive a unique identifier. FIG. 6 is a schematic diagram showing cross-sectional views of two exemplary groups of particles attached to a convex surface and an undulating surface, respectively. FIG. 7 is a schematic diagram, which is a plan view of an exemplary shape having a set of major and minor axes. FIG. 8 is a schematic plan view of exemplary shapes having a set of principal orthogonal axes, each including a major axis and a minor axis. FIG. 9 is a schematic diagram illustrating the relative distance and relative orientation between a pair of shapes defined by particles. FIG. 10 is a schematic diagram illustrating shapes defined by particles based on different perspectives. FIG. 11 is a schematic diagram illustrating shapes defined by multiple particles based on different perspectives. FIG. 12 is a flowchart illustrating an exemplary process for determining a unique code based on one or more images of an object containing particles. FIG. 13 is a flowchart illustrating an exemplary process for determining shape information based on one or more images of an object containing particles. FIG. 14 is a flowchart illustrating an exemplary process for determining relative position and relative orientation information for a pair of planar particles. FIG. 15 is a flowchart illustrating an exemplary process for determining two unique codes based on one or more images of an object containing planar particles each having sub-elements. FIG. 16 is a block diagram showing an exemplary device. In some embodiments, the particles have high aspect ratios, and as a result, each particle can be considered (or approximated) as a two-dimensional geometric object. For example, each particle may have physical ranges that occur primarily in two dimensions. In some cases, the thickness or depth of the particle is negligible relative to the particle size in either of the two major dimensions. For example, the thickness of the particle may be l