Optical Object Classification Using Characteristic Value Matching
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Solution Overview
Problem
Existing methods for assigning a usage object to a class are imprecise due to reliance on visual and technical details, leading to inaccuracies in object identification when comparing recorded objects with database entries.
Innovation Solution
A method involving a processing unit that captures and compares characteristic values of objects, using a camera to obtain and analyze parameters such as color, dimensions, and weight, and overlays camera images with database objects for precise classification, potentially using drones for efficient data capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If database comparison methods are used for object identification, then object classification can be performed, but identification accuracy deteriorates due to dependence on small optical and technical details
Solution Approach 1:
The patent extracts only the essential characteristic values (color, dimensions, weight) needed for object identification, eliminating unnecessary optical and technical details that cause comparison errors. This selective extraction of key features resolves the contradiction by maintaining identification accuracy while removing sources of unreliable comparison data
Solution Approach 2:
The patent changes the parameters used for object comparison from detailed optical and technical specifications to simplified characteristic values (color, dimensions, weight). This parameter transformation improves comparison reliability by focusing on stable, essential attributes while maintaining the ability to accurately identify and classify objects
2Loss of information
If detailed optical and technical comparison is performed, then object features can be analyzed, but identification accuracy deteriorates due to sensitivity to minor variations
Solution Approach 1:
The patent extracts only the essential characteristic values (color, dimensions, weight) needed for object identification, eliminating unnecessary optical and technical details that cause comparison errors. This selective extraction of key features resolves the contradiction by maintaining identification accuracy while removing sources of unreliable comparison data
Solution Approach 2:
Instead of comparing detailed optical and technical features as traditionally done, the patent inverts the approach by comparing simplified characteristic values. This inversion resolves the contradiction by showing that fewer, more essential parameters yield better identification precision without losing critical object information
3Productivity
If traditional database comparison methods are used, then object classification can be achieved, but the process becomes time-consuming and expensive
Solution Approach 1:
The patent changes the parameters used for object comparison from detailed optical and technical specifications to simplified characteristic values (color, dimensions, weight). This parameter transformation improves comparison reliability by focusing on stable, essential attributes while maintaining the ability to accurately identify and classify objects
Data Source
Figure 1~2A
Figure 2B~2C
Figure 3A~3B
AI summary
The invention relates to a method for the physical, in particular optical, detection of at least one object of use, comprising the step of carrying out at least one physical detection process, for example by a user and/or a device for carrying out the detection, in particular at least one photograph, of the object of use, such that the object of use is detected in such a way that an image of the object of use captured by the detection process is displayed simultaneously, identically or scaled identically to the database object displayed on a screen, wherein by the detection process the object of use is assigned by the processing unit and/or the CPU and/or the user to at least one class of object of use, for example a vehicle type.