3D Shape Measurement Using Material-Based Imaging Conditions
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Solution Overview
Problem
Conventional three-dimensional shape measurement systems struggle to appropriately set image pickup conditions for various types of objects, leading to issues like blown-out highlights or insufficient luminance, which hinder accurate shape measurement.
Innovation Solution
A three-dimensional shape measurement system that includes an image pickup unit, a storage device for condition information, and a measurement controller to identify the material and surface properties of the object, automatically adjusting image pickup conditions based on stored data and learning models to optimize imaging for accurate shape measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image pickup conditions are manually set by operators, then some objects can be measured, but it is difficult to specify appropriate conditions for various types of objects
Solution Approach 1:
The system performs self-identification of object material and surface properties, and automatically selects appropriate image pickup conditions without operator intervention. The measurement controller executes the identification process and condition selection autonomously based on captured images and stored reference data.
Solution Approach 2:
The system automatically adjusts image pickup parameters (exposure time, gain, illumination intensity) based on the identified material and surface properties of the object. Different parameter sets are selected from stored conditions corresponding to different material-surface property combinations.
2Illumination intensity
If strong light is used to illuminate the object, then image luminance improves, but blown-out highlights occur on reflective surfaces
Solution Approach 1:
The system applies different illumination intensities to different object types based on their material and surface properties. Highly reflective surfaces receive lower illumination intensity to prevent highlights, while diffuse surfaces receive higher intensity to ensure sufficient luminance.
Solution Approach 2:
The illumination intensity is dynamically adjusted based on the identified object properties. The system selects from multiple stored condition sets that correspond to different material-surface combinations, optimizing the balance between luminance and highlight prevention for each specific object type.
3Object-affected harmful factors
If insufficient light is used to illuminate the object, then blown-out highlights are avoided, but image luminance becomes too low to grasp surface shape
Solution Approach 1:
The system applies different illumination intensities to different object types based on their material and surface properties. Highly reflective surfaces receive lower illumination intensity to prevent highlights, while diffuse surfaces receive higher intensity to ensure sufficient luminance.
Solution Approach 2:
The illumination intensity is dynamically adjusted based on the identified object properties. The system selects from multiple stored condition sets that correspond to different material-surface combinations, optimizing the balance between luminance and highlight prevention for each specific object type.
4Measurement precision
If image pickup conditions are customized for each object type, then measurement accuracy improves, but system complexity increases
Solution Approach 1:
The system pre-stores multiple sets of image pickup conditions corresponding to different material and surface property combinations. This preliminary preparation eliminates the need for complex real-time calculations and simplifies the measurement process to automatic identification and condition selection.
Solution Approach 2:
The system creates a universal database of image pickup conditions that can be applied to various object types. By categorizing conditions based on material and surface properties, the system achieves multi-functionality across different measurement scenarios without requiring separate customization for each object.
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
Enables accurate and simplified shape measurement of diverse objects by automatically adjusting image pickup conditions, overcoming issues of blown-out highlights and low luminance, thereby improving measurement precision and ease of use.
Implementation Method 1
an image pickup unit configured to have at least one camera that images an object
Data Source
AI summary
A three-dimensional shape measurement system includes an image pickup unit, a storage device that stores image pickup conditions required in imaging for measurement as condition information for each of a plurality of combinations of the material and surface property of an object, and a measurement controller that controls driving of the image pickup unit. The measurement controller identifies the material and surface property of the object, specifies image pickup conditions corresponding to the identified material and surface property of the object based on the condition information, causes the image pickup unit to perform the imaging for measurement under the specified image pickup conditions, and measures the shape of the object based on the obtained image for measurement.