3D Object Identification via Multi-Angle Image Superposition
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Solution Overview
Problem
Current methods for identifying objects through digital scanning of image portions are inefficient due to variations in scanning and capture angles caused by operator movements, leading to inconsistent data capture and potential misidentification of objects.
Innovation Solution
The method involves generating multiple image data records with varying scanning and capture angles, superposing these records to remove unwanted reflections, and capturing points based on deviations in characteristics, using a grid for focused scanning, and considering operator inputs and environmental factors to create unique digital images for fast identification and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital scanning is performed with fixed scanning and capture angles, then measurement precision is improved, but device complexity increases due to the need for precise positioning systems
Solution Approach 1:
The patent applies the dynamics principle by making the scanning and capture angles variable rather than fixed. The system dynamically adjusts scanning angles and capture angles independently, allowing the imaging device to adapt to different object geometries and scanning requirements without requiring complex fixed positioning systems for every possible angle configuration.
Solution Approach 2:
The patent segments the scanning process into multiple independent angular dimensions. Instead of treating the scanning system as a single complex positioning unit, it divides the angular space into separable scanning angles and capture angles that can be controlled and adjusted independently, simplifying the overall system architecture.
2Reliability
If multiple image data records with varying angles are generated, then object identification accuracy is improved, but loss of time increases due to multiple scanning operations
Solution Approach 1:
The patent implements continuous useful action by performing multiple scans at different angles without requiring full completion and processing of each individual scan before starting the next. The system continuously accumulates image data records from multiple angular perspectives, enabling parallel data collection that reduces total scanning time while maintaining identification accuracy.
Solution Approach 2:
The system performs preliminary scanning actions to capture image data at multiple angles before final object identification is executed. This preliminary multi-angle data collection prepares comprehensive information in advance, allowing faster and more accurate identification in the subsequent processing stage.
3Measurement precision
If all points of the image are captured digitally, then measurement precision is improved, but quantity of substance increases leading to higher data processing requirements
Solution Approach 1:
The patent applies local quality by capturing digital information selectively at specific points rather than uniformly across the entire image. The system identifies and captures data at points where geometric features or changes in object characteristics occur, allocating data capture resources locally where they are most needed for accurate object identification.
Solution Approach 2:
The system performs partial action by capturing only the necessary portion of image points required for identification. Instead of digitally capturing all points in the image, it selectively captures points that provide sufficient information for object identification, reducing data volume while maintaining measurement precision.
Data Source
AI summary
Identification of objects, in particular three dimensional objects, includes digital scanning of at least one image portion of an image of at least one object to be identified for the digital capture of points of the image. The digitally captured points of the at least one image portion of the image are combined to form an image data record, wherein multiple image data records are generated for the object to be identified, and the image data records differ from one another at least in view of at least one image portion characteristic.