Free-Fall Imaging Sphere for 3D Surface Capture
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Solution Overview
Problem
Existing methods for imaging three-dimensional surfaces of objects, such as spheres or cubes, face challenges including latency in sequential imaging and incompleteness due to mechanical obstructions when using multiple cameras with overlapping fields of view.
Innovation Solution
A system and method involving an imaging apparatus with a frame, an imaging sphere, detectors, and multiple imaging sensors that allow for simultaneous imaging of an object in free fall, triggering cameras to capture images from multiple angles without rotation, enabling complete and efficient capture of a three-dimensional surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If sequential imaging method is used to image three-dimensional surface, then imaging completeness is improved, but imaging speed deteriorates
Solution Approach 1:
The object is allowed to move freely through the imaging chamber rather than being held stationary and rotated mechanically. The free-fall motion creates dynamic imaging conditions where multiple cameras capture the object from different angles as it passes through, achieving complete surface imaging without mechanical rotation constraints
Solution Approach 2:
The mechanical rotation system is replaced with a gravity-based free-fall system. Instead of using motors and mechanical fixtures to rotate the object, the invention uses gravitational force to naturally move the object through the imaging zone, eliminating mechanical complexity and enabling simultaneous multi-angle capture
2Productivity
If multiple cameras with overlapping fields of view are used, then imaging speed is improved, but imaging completeness deteriorates due to mechanical obstruction
Solution Approach 1:
The object is extracted from mechanical fixtures and allowed to move freely through the imaging chamber. By removing the mechanical holding system, the invention eliminates the obstruction problem that prevents complete surface imaging with multiple cameras, enabling all cameras to capture the entire object surface simultaneously
Solution Approach 2:
The imaging system transitions from a two-dimensional rotation approach to a three-dimensional free-fall approach. Multiple cameras positioned at different heights and angles capture the object as it moves vertically through the chamber, providing complete surface coverage without mechanical obstructions
3Ease of operation
If mechanical fixture is used to hold and rotate object, then imaging control is improved, but imaging completeness deteriorates due to obstruction
Solution Approach 1:
The object performs its own positioning and orientation through natural free-fall motion under gravity. Instead of requiring external mechanical fixtures to control and rotate the object, the system uses the object's own gravitational movement to achieve optimal imaging positions, eliminating obstruction while maintaining imaging control
Solution Approach 2:
Gravity acts as an intermediary force to control object motion instead of mechanical fixtures. The gravitational field naturally guides the object through the imaging chamber, providing smooth, obstruction-free movement that enables complete surface imaging from multiple angles
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for faster, more complete, and efficient imaging of three-dimensional surfaces without obstructions, providing a simpler and more integrated automation solution.
Implementation Method 1
the passing of the object through the imaging sphere includes free falling through the imaging sphere
Implementation Method 2
free falling through the imaging sphere
Data Source
AI summary
A system and method for acquiring an image. The method includes dropping an object into free fall, detecting the dropping of the object, triggering a plurality cameras to simultaneously image the object in parallel, while the object drops into a bottom half of an imaging sphere at a center of a field of view of each of the plurality of cameras, upon detecting the dropping of the object, analyzing images of the imaged object in parallel, based on a trained machine learning model, and displaying a three dimensional image of a surface of the object based on the analysis of the images of the imaged object.