# US 12,602,903 B2 · Method for analyzing image information using assigned scalar values > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,602,903 B2 - Document ID: US12602903B2 - Status: Granted - Kind: B2 - Application number: 17/641,703 - Filed: 2019-09-11 - Published: 2022-09-22 - Granted: 2026-04-14 - Earliest claimed: 2019-09-11 - Assignees: Siemens Aktiengesellschaft - Applicants: Siemens Aktiengesellschaft - Inventors: Jonas Witt - Web page: https://patentgrep.com/patent/US12602903B2 ## CPC - G06T 7/001: {using an image reference approach} - G06V 10/751: {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching} - G06V 10/762: using clustering, e.g. of similar faces in social networks - G06V 10/776: Validation; Performance evaluation - G06V 10/82: using neural networks - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/30108: Industrial image inspection - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A method for analyzing image information using assigned scalar values includes a.) capturing a first image of an object or a situation and capturing at least one first scalar sensor value relating to the object or the situation; b.) capturing a second image of the object or the situation and capturing at least one second scalar sensor value relating to the object or the situation; c.) inserting the first image and the at least one first scalar sensor value into a first data structure as a consistent representation form, and inserting the second image and the at least one second scalar sensor value into a second data structure as a consistent representation form; d.) comparing the first and the second data structure and e.) outputting information if the comparison results in a difference that corresponds to a defined or definable criterion. ## Claims ### Claim 1 A method for analyzing image information utilizing assigned scalar values to increase a reliability of an analysis of the image information, the method comprising: a.) capturing a first image of an object or a situation and capturing at least one first scalar sensor value relating to the object or the situation; b.) capturing a second image of the object or the situation and capturing at least one second scalar sensor value relating to the object or the situation; c.) inserting the first image and the at least one first scalar sensor value as a consistent representational form into a first data structure, and inserting the second image and the at least one second scalar sensor value as a consistent representational form into a second data structure; d.) comparing the first data structure and the second data structure to determine whether the comparison reveals a difference corresponding to a predefined or predefinable criterion to increase the reliability of the analysis of the image information; and e.) outputting an item of information if the comparison reveals the difference corresponding to the predefined or predefinable criterion; wherein the method is configured to monitor a method sequence or production sequence such that the capture of the first image and the second image is configured as the capture of a first and a second image of an object relating to the production sequence or a situation relating to the production sequence, and such that the capture of the at least one first and second scalar sensor value is configured as the capture of at least one first and at least one second scalar sensor value relating to the object relating to the production sequence or the situation relating to the production sequence; wherein the production sequence is configured to produce a product and comprises a sequence of production steps, an intermediate product existing after a selected production step from the sequence of production steps has been performed; wherein the first image is also configured as a first intermediate product image, the at least one first scalar sensor value relates to the selected production step, the second image is configured as a second intermediate product image, and the at least one second scalar sensor value relates to the selected production step; and wherein the first data structure and the second data structure are compared via a neural network. ### Claim 2 (depends on 1) The method as claimed in claim 1, wherein the respectively captured image is respectively transformed to the frequency domain to create the first data structure and the second data structure. ### Claim 3 (depends on 2) The method as claimed in claim 2, wherein at least one first scalar parameter value relating to the object or situation is also captured within method step a.); wherein at least one second scalar parameter value relating to the object or situation is also captured within method step b.); and wherein the first data structure and the second data structure are also created utilizing the at least one first scalar parameter value and the at least one second parameter value. ### Claim 4 (depends on 1) The method as claimed in claim 1, wherein the respectively captured image is respectively transformed to the frequency domain via a Fourier analysis method. ### Claim 5 (depends on 1) The method as claimed in claim 1, wherein at least one first scalar parameter value relating to the object or situation is also captured within method step a.); wherein at least one second scalar parameter value relating to the object or situation is also captured within method step b.); and wherein the first data structure and the second data structure are also created utilizing the at least one first scalar parameter value and the at least one second parameter value. ### Claim 6 (depends on 1) The method as claimed in claim 1, wherein the first data structure and the second data structure one of (i) each have a two-dimensional or higher-dimensional diagram structure or a two-dimensional or higher-dimensional graph structure and (ii) are each represented or representable as a two-dimensional or higher-dimensional diagram or a two-dimensional or higher-dimensional graph. ### Claim 7 (depends on 6) The method as claimed in claim 6, wherein one of (i) a clustering method has been or is respectively applied to respective diagrams, graphs, diagram structures or graph structures of the first and second data structures when creating the first data structure and the second data structure in accordance with method step c.) and (ii) a clustering method is respectively applied to the respective diagrams, graphs, diagram structures or graph structures of the first and second data structures when comparing the first data structure and the second data structure in accordance with method step d.). ### Claim 8 (depends on 1) The method as claimed in claim 1, wherein, within method step c.), the first data structure is created utilizing at least one further first production parameter value, and the second data structure is created utilizing at least one further second production parameter value. ### Claim 9 (depends on 1) The method as claimed in claim 1, wherein the method is configured to monitor the movement of a vehicle in such that the capture of the first image and the second image is configured as the capture of a first image and a second image of an environment detail of the vehicle, and such that the capture of the at least one first sensor value and the at least one second sensor value is configured as the capture of at least one first sensor value and at least one second sensor value relating to the vehicle or an environment of the vehicle. ### Claim 10 (depends on 1) The method as claimed in claim 1, wherein the method is configured to analyze an image of an object or a living being such that the capture of the first image and the second image is configured as the capture of a first image and a second image of the living being or object or an area thereof in each case, and such that the capture of the at least one first sensor value and the at least one second sensor value is configured as the capture of at least one first sensor value and at least one second sensor value relating to the living being or object or the area thereof in each case.