Optical Context Recognition for Interchangeable Lenses
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Solution Overview
Problem
Existing methods for determining contextual information in optical systems with interchangeable components are complex, energy-intensive, and require modifications to the components, leading to increased costs and susceptibility to errors, especially in automated systems like high-end microscope stands and digital recordings.
Innovation Solution
A method that captures images of interchangeable components using a camera, either fixed or portable, to determine contextual information through machine learning algorithms, such as convolutional neural networks, without modifying the components, allowing for accurate recognition of types, operating parameters, and anomalies under varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If wireless transponders, magnetism, capacitances, sliding contacts, NFC, or ACR techniques are used to determine contextual information, then automated determination is achieved, but device complexity and energy demand increase
Solution Approach 1:
The patent uses optical copying by capturing images of interchangeable components with a camera. Instead of complex electronic transmission apparatus, the system creates visual copies (images) of components and processes these images computationally to extract contextual information, thereby simplifying hardware while maintaining automation.
Solution Approach 2:
The patent replaces mechanical/electronic transmission systems (wireless transponders, NFC, sliding contacts) with an optical-computational system. A camera captures images and computer algorithms process them to determine contextual information, substituting complex electronic mechanisms with simpler optical sensing and software processing.
2Extent of automation
If wireless transponders, magnetism, capacitances, sliding contacts, NFC, or ACR techniques are used to determine contextual information, then automated determination is achieved, but energy consumption increases
Solution Approach 1:
The system creates optical copies (images) of components using a camera, which consumes minimal energy compared to active electronic transmission devices. The captured images are then processed computationally to extract contextual information without requiring continuous energy-intensive transmission operations.
Solution Approach 2:
The patent substitutes energy-intensive electronic transmission systems with passive optical imaging and computational processing. The camera-based approach requires significantly less energy than maintaining wireless transponders, NFC communicators, or other active electronic identification systems.
3Extent of automation
If interchangeable components are modified to include transmission apparatus, then automated determination of contextual information is achieved, but manufacturing costs increase
Solution Approach 1:
The camera-based system serves multiple functions: it captures images for contextual information extraction, documents component states, and can identify various types of interchangeable components without requiring different hardware modifications. This universal approach eliminates the need for component-specific transmission apparatus.
Solution Approach 2:
Instead of modifying components with expensive electronic transmission devices, the system uses optical copying to capture images of components in their native state. This approach requires no modification to interchangeable components, thereby maintaining ease of manufacture and reducing costs.
4Device complexity
If manual input of contextual information is required, then no additional hardware is needed, but operator control complexity and error susceptibility increase
Solution Approach 1:
The system enables self-service by automatically capturing images of interchangeable components and extracting contextual information through computational processing. This eliminates the need for manual operator input, reducing both hardware complexity and operational complexity while minimizing human error.
Solution Approach 2:
The patent replaces manual operator input with an automated optical-computational system. A camera captures images and software algorithms automatically extract contextual information, substituting human operators with a streamlined electronic-imaging system that reduces complexity and error susceptibility.
Data Source
AI summary
At least one image is obtained which images an external view of at least one interchangeable component (111-116) of an optical system (100). Contextual information for the at least one interchangeable component (111-116) is determined on the basis of the at least one image.