# US 2025/0095335 A1 · Image manipulation for material information determination > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0095335 A1 - Document ID: US20250095335A1 - Status: Published application - Kind: A1 - Application number: 18/728,129 - Filed: 2023-02-13 - Published: 2025-03-20 - Earliest claimed: 2022-02-15 - Assignees: Trinamix GmbH - Applicants: Trinamix GmbH - Inventors: Peter SCHILLEN; Benjamin GUTHIER; Nicolas WIPFLER; Patrick SCHINDLER - Web page: https://patentgrep.com/patent/US20250095335A1 ## CPC - G06V 10/7715: {Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods} - G06V 10/145: Illumination specially adapted for pattern recognition, e.g. using gratings - G06V 10/60: relating to illumination properties, e.g. using a reflectance or lighting model - G06V 10/762: using clustering, e.g. of similar faces in social networks - G06V 10/774: Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting - G06V 10/82: using neural networks - G06V 40/168: {Feature extraction; Face representation} - G06V 40/172: {Classification, e.g. identification} - G06V 40/40: Spoof detection, e.g. liveness detection - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract Disclosed herein is a method for extracting material information of an object from a pattern image of the object. The pattern image showing the object while the object is illuminated with a light pattern is received. The pattern image is manipulated to generate a partial image from the pattern image. Material information of the object is extracted from the partial image by providing the partial image to a data-driven model. The data-driven model is parametrized according to a training data set including partial images and material information. The extracted material information is provided. ## Claims ### Claim 1 A computer implemented method for extracting material information of an object from a pattern image of the object, wherein the method comprises: receiving the pattern image showing the object while the object is illuminated with a light pattern; manipulating the pattern image to generate a partial image from the pattern image; extracting material information of the object from the partial image by providing the partial image to a data-driven model, wherein the data-driven model is parametrized according to a training data set including partial images and material information; and providing the extracted material information. ### Claim 2 (depends on 1) The method according to claim 1, wherein the pattern illumination is a regular pattern and/or a periodic pattern and/or a dot pattern and/or speckle pattern, with pattern features-and/or dots and/or speckles per face area at a distance of 5-200 cm. ### Claim 3 (depends on 1) The method according to claim 1, wherein a pattern in the pattern image results from the object being illuminated with the pattern illumination, and/or wherein the pattern image comprises contributions from reflections of the pattern illumination and/or from a texture of the object. ### Claim 4 (depends on 1) The method according to claim 1, wherein the partial image comprises at least parts of at least one pattern feature. ### Claim 5 (depends on 1) The method according to claim 1, wherein the material information is derived from reflections of the pattern illumination. ### Claim 6 (depends on 1) The method according to claim 1, wherein the object is a face and/or wherein the material information comprises a material class, a material structure, a material property and/or a material type. ### Claim 7 (depends on 1) The method according to claim 1, wherein the step of extracting material information of the object from the partial image further comprises providing the partial image to a data-driven model, wherein the data-driven model is parametrized according to the training data set further comprising the representation of one or more of the partial images and/or the cluster of one or more of the partial images, and wherein the data-driven model is parameterized to extract the material information. ### Claim 8 (depends on 7) The method according to claim 7, wherein the training of the data-driven model comprises determining a representation of the partial image, wherein the representation is associated with a physical signature embedded in the reflections of the pattern illumination in the partial image. ### Claim 9 (depends on 8) The method according to claim 8, wherein the partial image is part of a data set of partial images; and wherein a cluster is derived via clustering of the partial images of the data set based on the representation, wherein the cluster is associated to the representation. ### Claim 10 An apparatus for extracting material information of an object from a pattern image of the object, wherein the apparatus comprises: a receiving unit configured to receive the pattern image showing the object; a manipulating unit configured to manipulate the pattern image to generate a partial image; an extracting unit configured to extract material information of the object from the partial image by providing the partial image to a data-driven model, wherein the data-driven model is parametrized according to a training data set including partial images and material information; and a provisioning unit configured to provide the extracted material information. ### Claim 11 A computer implemented method for training a data-driven model suitable for extracting material information of an object from a pattern image of the object, wherein the method comprises: receiving the pattern image showing the object while the object is illuminated with a light pattern; manipulating the pattern image to generate a partial image; training a data-driven model to determine material information of the object from the partial image, wherein the training comprises parametrizing the data-driven model according to a training data set including partial images and material information, and providing the trained data-driven model. ### Claim 12 An apparatus for training a data-driven model suitable for extracting material information of an object from a pattern image of the object, wherein the method comprises: a receiving unit configured to receive the pattern image showing the object; a manipulating unit configured to manipulate the pattern image to generate a partial image; a training unit configured to train a data-driven model to determine material information of the object from the partial image, wherein the training comprises parametrizing the data-driven model according to a training data set including partial images and material information, and a provisioning unit configured to provide the trained data-driven model. ### Claim 13 (depends on 1) A computer program for extracting material information of an object from a pattern image of the object, the computer program including instructions causing a computer to execute the steps of the method according to claim 1. ### Claim 14 A data structure product comprising manipulated image data for extracting material information from a pattern image, wherein the manipulated image data includes partial images; and/or at least one representation associated with a physical signature of the partial image; and/or at least one cluster associated with the representation and/or material information labelling the pattern features in the pattern image. ### Claim 15 (depends on 14) A method of using the manipulated data according to claim 14 the method comprising using the manipulated data to authenticate an object. ### Claim 16 (depends on 1) A method of using the manipulated data obtained by the method according to claim 1, the method comprising using the manipulated data to authenticate an object. ### Claim 17 (depends on 1) The method according to claim 1, wherein the pattern illumination is a regular pattern and/or a periodic pattern and/or a dot pattern and/or speckle pattern with at least 2 pattern features and/or dots and/or speckles per face area at a distance of 30-60 cm. ### Claim 18 (depends on 1) The method according to claim 1, wherein the pattern illumination is a regular pattern and/or a periodic pattern and/or a dot pattern and/or speckle pattern with at least 6 pattern features and/or dots and/or speckles per face area at a distance of 15-80 cm. ### Claim 19 (depends on 1) A method of using the manipulated data obtained by the method according to claim 1, the method comprising using the manipulated data to biometrically authenticate an object. ### Claim 20 (depends on 11) A method of using the trained data-driven model obtained by the method according to claim 11, the method comprising using the trained data-driven model to biometrically authenticate an object.