Object-Based Access Control Using Image Feature Matching
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Solution Overview
Problem
The increasing volume of sensor data from smart devices and manufacturing installations poses challenges in securely and efficiently managing and accessing control functions for these devices.
Innovation Solution
A device comprising a capture module for capturing individual features of an object, a checking module for comparing these features with a reference value, and a control module that grants access to control functions based on a sufficiently accurate match, ensuring secure access and data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional access control methods are used for smart devices and manufacturing installations, then device complexity is reduced, but data security and authorization reliability deteriorate
Solution Approach 1:
The patent introduces a capture device as an intermediary component that captures images of objects and transmits them to a computing device for processing. This intermediary handles the complex tasks of image processing, feature extraction, and comparison against reference values, thereby maintaining high security while preventing the access control system itself from becoming overly complex. The capture device acts as a buffer between the physical object and the digital access control system.
Solution Approach 2:
The patent replaces traditional mechanical or manual access control methods (such as physical keys, cards, or biometric scanners) with an image-based recognition system. Instead of relying on physical authentication mechanisms, the system captures visual features of objects, extracts relevant characteristics, and compares them digitally against stored reference values. This substitution enables more reliable and flexible access control while maintaining manageable system complexity through software-based processing.
2Productivity
If manual verification of object features is used, then measurement precision is sufficient, but productivity and time efficiency deteriorate
Solution Approach 1:
The patent replaces manual verification of object features with automated image processing and computer vision algorithms. The capture device captures images, and the computing device automatically extracts features, compares them against reference values, and makes access decisions. This automation dramatically increases processing speed and productivity while maintaining high measurement precision through sophisticated algorithms that can detect subtle features and patterns that would be difficult for humans to identify consistently.
Solution Approach 2:
The patent creates digital copies of object features through image capture and processing. Instead of manually examining physical objects, the system creates digital representations (images) of the objects, extracts relevant features from these copies, and compares the feature copies against stored reference copies. This copying approach enables rapid automated processing while maintaining precision through consistent digital measurement standards.
3Reliability
If comprehensive object feature capture is implemented, then authorization reliability improves, but device complexity and processing requirements worsen
Solution Approach 1:
The patent extracts only the essential and relevant features from captured images rather than processing all image data. The computing device identifies and extracts specific object features that are sufficient for accurate identification and authorization, discarding unnecessary information. This extraction approach maintains high authorization reliability by focusing on critical identifying characteristics while reducing processing complexity and computational requirements by eliminating redundant data processing.
Data Source
AI summary
To separate excess material from an additively manufactured component, spatially resolved structural data on the component are received. On the basis of the structural data, a cavity of the component is divided by a virtual spatial grid into grid cells, wherein a spatial orientation of the grid relative to the component is specified by an orientation specification. On the basis of the orientation specification, a discrete grid of spatial orientations of the component is determined. Furthermore, the grid cells of the cavity are simulatively filled with virtual material. On the basis of the structural data, an emptying process of the virtual material from the component for spatial orientations limited to the discrete grid is then simulated, wherein a temporal sequence of orientations limited to the discrete grid is then determined. According to the simulated emptying process, the component is then successively rotated into the orientations of the temporal sequence.