Detector for identifying at least one material property

Patent metadata

Field	Value
Publication number	US-11947013-B2
Application number	US-202017439492-A
Country	US
Kind code	B2
Filing date	Mar 13, 2020
Priority date	Mar 15, 2019
Publication date	Apr 2, 2024
Grant date	Apr 2, 2024

Abstract

Described herein is a detector for identifying at least one material property m. The detector includes at least one sensor element including a matrix of optical sensors, the optical sensors each having a light-sensitive area. The sensor element is configured for recording at least one reflection image of a light beam originating from at least one object. The detector includes at least one evaluation device configured for determining the material property by evaluation of at least one beam profile of the reflection image.

First claim

The invention claimed is:

1. A detector for identifying at least one material property m comprising
at least one sensor element comprising a matrix of optical sensors, the optical sensors each having a light-sensitive area, wherein the sensor element is configured for recording at least one reflection image of a light beam originating from at least one object, and
at least one evaluation device configured for determining the material property by evaluation of at least one beam profile of the reflection image,
wherein the evaluation device is configured for determining at least one distance feature φ 1z by applying at least one distance dependent image filter Φ 1 to the reflection image, wherein the distance dependent image filter is at least one filter selected from the group consisting of: a depth-from-photon-ratio filter; a depth-from-defocus filter, or a linear combination thereof; and a further distance dependent image filter Φ 1other which correlates to the depth-from-photon-ratio filter and/or the depth-from-defocus filter or a linear combination thereof by |ρ Φ1other,Φz |≥0.40 with Oz being one of the depth-from-photon-ratio filter or the depth-from-defocus filter or a linear combination thereof,
wherein the evaluation device is configured for determining at least one material feature φ 2m by applying at least one material dependent image filter Φ 2 to the reflection image, wherein the material dependent image filter is at least one filter selected from the group consisting of a luminance filter; a spot shape filter; a squared norm gradient: a standard deviation; a smoothness filter; a Gaussian filter or median filter; a grey-level-occurrence-based contrast filter, a grey-level-occurrence-based energy filter, a grey-level-occurrence-based homogeneity filter; a grey-level-occurrence-based dissimilarity filter: a Law's energy filter; a threshold area filter; or a linear combination thereof, and a further material dependent image filter Φ 2other which correlates to one or more of the luminance filter, the spot shape filter, the squared norm gradient, the standard deviation, the smoothness filter, the grey-level-occurrence-based energy filter, the grey-level-occurrence-based homogeneity filter, the grey-level-occurrence-based dissimilarity filter, the Law's energy filter, or the threshold area filter, or a linear combination thereof by |ρ Φ2other,Φm |≥0.40 with Φ m being one of the luminance filter, the spot shape filter, the squared norm gradient, the standard deviation, the smoothness filter, the grey-level-occurrence-based energy filter, the grey-level-occurrence-based homogeneity filter, the grey-level-occurrence-based dissimilarity filter, the Law's energy filter, or the threshold area filter, or a linear combination thereof, and
wherein the evaluation device is configured for determining a longitudinal coordinate z and the material property m by evaluating the distance feature φ 1z and the material feature φ 2m .

2. The detector according claim 1 , wherein the material dependent image filter is at least one filter that passes a hypothesis testing, wherein the hypothesis testing uses a Null-hypothesis that the filter does not distinguish between material classifiers and an alternative hypothesis that the filter distinguishes at least two material classifiers, wherein the filter passes the hypothesis testing if a p-value, p, is smaller or equal than a pre-defined level of significance.

3. The detector according to claim 1 , wherein p≤0.075.

4. The detector according to claim 1 , wherein the at least one material property is a property selected from the group consisting of a scattering coefficient, a translucency, a transparency, a deviation from a Lambertian surface reflection, and a speckle.

5. The detector according to claim 1 , wherein the further distance dependent image filter Φ 1other correlates to one or more of the distance dependent image filters Φ z by |ρ 1other,Φz |≥0.60.

6. The detector according to claim 1 , wherein the further material dependent image filter Φ 2other correlates to one or more of the material dependent image filters Φ m by |ρ Φ2other,Φm |≥0.60.

7. The detector according to claim 1 , wherein the material property m and/or the longitudinal coordinate z are determined by using a predetermined relationship between φ 1z , φ 2m and z, m.

8. The detector according to claim 1 , wherein the material property m and/or the longitudinal coordinate z are determined by a function z(φ 1z , φ 2m ) and/or m(φ 1z , φ 2m ).

9. The detector according to claim 1 , wherein the evaluation device is configured for applying the distance dependent image filter and the material dependent image filter simultaneous to the reflection image.

10. The detector according to claim 1 , wherein the evaluation device is configured for determining whether at least one of Φ 1 or Φ 2 is a function of the feature φ 1z or φ 2m of the other image filter or whether at least one of Φ 1 or Φ 2 is a function of the at least one other image filter, wherein the evaluation device is configured for applying the distance dependent image filter and the material dependent image filter sequentially or recursively to the reflection image.

11. The detector according to claim 10 , wherein the evaluation device is configured for determining at least one of z and/or m by applying at least one further filter depending on at least one of φ 1z and φ 2m to the reflection image.

12. The detector according to claim 1 , wherein the depth-from-photon-ratio filter comprises evaluating a combined signal Q from at least two sensor signals of the sensor element, wherein the evaluation device is configured for deriving the combined signal Q by one or more of dividing the sensor signals, dividing multiples of the sensor signals, dividing linear combinations of the sensor signals, wherein the evaluation device is configured for using at least one predetermined relationship between the combined signal Q and the distance feature φ 1z for determining the distance feature φ 1z .

13. The detector according to claim 1 , wherein the depth-from-defocus filter comprises using at least one convolution-based algorithm such as a depth-from-defocus algorithm, wherein the evaluation device is configured for determining the distance feature φ 1z by optimizing at least one blurring function f a , wherein the blurring function is optimized by varying the parameters of the at least one blurring function.

14. The detector according to claim 1 , wherein the sensor element comprises at least one CMOS sensor.

15. The detector according to claim 1 , wherein the detector comprises at least one illumination source, wherein the illumination source is configured for generating at least one illumination pattern for illumination of the object, wherein the illumination pattern comprises at least one pattern selected from the group consisting of: at least one point pattern, in particular a pseudo-random point pattern; a random point pattern or a quasi random pattern, at least one Sobol pattern; at least one quasiperiodic pattern; at least one pattern comprising at least one pre-known feature; at least one regular pattern, at least one triangular pattern; at least one hexagonal pattern; at least one rectangular pattern; at least one pattern comprising convex uniform tilings, at least one line pattern comprising at least one line; at least one line pattern comprising at least two lines; and at least one line pattern comprising parallel or crossing lines.

16. The detector ( 110 ) according to claim 15 , wherein the illumination source comprises at least one laser

Assignees

• Trinamix Gmbh

Inventors

• Schick Friedrich
• Schillen Peter
• Schindler Patrick
• Schmidt Andre
• Eberspach Michael
• Lennartz Christian
• Send Robert
• Diesselberg Lars
• Hengen Heiko
• Bruder Ingmar
• Unger Jakob
• Bonsignore Christian

Classifications

• H04N23/74

  by influencing the scene brightness using illuminating means · CPC title

• H04N23/56

  provided with illuminating means · CPC title

• G06V20/95

  Pattern authentication; Markers therefor; Forgery detection · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06V10/60

  relating to illumination properties, e.g. using a reflectance or lighting model · CPC title