Optical Usage Object Identification Through Multi-Image Database Matching
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Solution Overview
Problem
Existing methods for identifying usage objects are inaccurate due to reliance on optical and data-related details, leading to errors in comparison with database entries, and are not cost-effective or time-efficient.
Innovation Solution
A method involving a portable processing unit with a camera that captures and compares characteristic values of usage objects with database entries, using a combination of optical and data-related analysis to achieve unique and biunique identification, potentially with the aid of drones for efficient image capture and virtual marking elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optical detection methods are used to identify usage objects, then the process is simple and low-cost, but the accuracy is poor due to sensitivity to small optical and data-related details
Solution Approach 1:
The patent uses multiple captured images of the usage object to create a composite representation that is then compared against database entries. By copying and processing multiple views of the object rather than relying on a single optical snapshot, the system achieves higher identification accuracy while managing complexity through software-based processing
Solution Approach 2:
The patent segments the identification process into distinct steps: capturing multiple images, processing them to extract characteristic values, comparing with database entries, and making identification decisions. This segmentation allows each component to be optimized independently, improving overall accuracy without proportionally increasing system complexity
2Reliability
If detailed optical and data-related analysis is performed to improve identification accuracy, then uniqueness of identification increases, but the time required for processing increases
Solution Approach 1:
The patent performs preliminary processing of captured images to extract key characteristic values before comparison with database entries. By pre-processing and pre-extracting relevant features, the system reduces the computational burden during the actual comparison phase, thereby maintaining high reliability while reducing overall processing time
Solution Approach 2:
The patent applies a balance between detailed analysis and processing efficiency by focusing on the most discriminative characteristic values rather than analyzing every possible feature. This partial action approach maintains unique identification reliability by concentrating on key distinguishing features while avoiding unnecessary processing of less relevant details
3Measurement precision
If multiple characteristic values are extracted and compared with database entries to ensure accurate identification, then the precision of object classification improves, but the complexity of data processing increases
Solution Approach 1:
The patent introduces an intermediary processing layer that extracts characteristic values from captured images and serves as a mediator between the raw optical data and the database comparison process. This intermediary step simplifies the data structure and reduces complexity by transforming complex image data into standardized characteristic values that are easier to process and compare
Data Source
AI summary
Disclosed is a method for the physical, in particular optical, detection of at least one usage object. The method includes the step of carrying out at least one physical detection process, for example by a user and/or an implementation device, in particular of at least one photograph, of the usage object, so that the usage object may be detected in such a way that an image of the usage object as detected during the detection process is shown at the same time as the database object shown on the screen in an identical manner or in a manner identical to scale, wherein as a result of the detection process, the usage object is associated with at least one usage object class, for example a vehicle type, by the processing unit and/or the CPU and/or the user.