Imaging Condition Setting Rule Generator for Object Discrimination
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Solution Overview
Problem
Existing methods for setting imaging conditions in visual sensors used by robots to identify objects with varying positions, postures, or types are inefficient, requiring extensive calculations and being slow to adjust when incorrect discrimination results are obtained, making it difficult to quickly set optimal imaging conditions.
Innovation Solution
An imaging apparatus and method that includes an image pickup unit, an object discriminating unit, a discriminable range generator, an identification determination result range generator, an imaging condition setting rule generator, and a setting unit, which together quickly adjust imaging conditions by generating and applying rules based on discriminable and identification determination ranges to ensure accurate object discrimination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mutual entropies for all imaging conditions are acquired by simulating the results online, then the accuracy of object discrimination is improved, but the calculation time increases and the speed of setting imaging conditions deteriorates
Solution Approach 1:
The patent pre-calculates and stores mutual entropy values for all possible imaging conditions in advance, creating a lookup table that can be quickly referenced during actual operation. This eliminates the need for time-consuming online simulations while maintaining discrimination accuracy, as the system can directly query pre-computed values based on current object characteristics.
Solution Approach 2:
The patent extracts only the essential features and characteristics of the object from the full image data to determine imaging conditions. By focusing on key discriminative features rather than processing complete image information, the system reduces calculation complexity and enables faster condition setting while preserving the accuracy needed for proper object discrimination.
2Loss of information
If the camera is actively controlled to image the object from a plurality of viewpoints, then the information acquired for object discrimination is improved, but the complexity of the imaging system increases
Solution Approach 1:
The patent determines that a single strategically selected viewpoint is sufficient for accurate object discrimination by using pre-calculated mutual entropy information. Instead of requiring multiple viewpoints, the system identifies the optimal single imaging condition from pre-computed data, reducing system complexity while obtaining adequate information for discrimination.
Solution Approach 2:
The patent introduces a calculation unit that acts as an intermediary, using pre-stored mutual entropy data to determine the optimal imaging condition. This intermediary layer processes object characteristics and queries the pre-computed lookup table, eliminating the need for complex active control mechanisms while still achieving informed imaging condition selection.
Data Source
AI summary
According to the present invention, an imaging condition setting method includes an object discriminating step S1-1 of discriminating the object by using images, a discriminable range generating step S1-2 of generating a discriminable range that is a range of the imaging conditions under which the object is discriminable, an identification determination result range generating step S1-2 of generating an identification determination result range that is a range of the imaging conditions under which the objects are determined as identical, an imaging condition setting rule generating step S1-4 of generating an imaging condition setting rule that is a rule for changing an imaging condition by using the discriminable range and the identification determination result range, and an imaging condition setting step S2-4 of setting an imaging condition under which the object is discriminable by using the imaging condition setting rule generated by the imaging condition setting rule generating step.