Object Recognition System with Dynamic Light Control
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Solution Overview
Problem
Existing object recognition systems face challenges in maintaining recognition precision due to changes in luminance or color in captured images caused by light source flashing, and require high-performance devices to manage clock differences between sensors and imaging devices, leading to increased costs and processing loads.
Innovation Solution
An object recognition system that includes detection, imaging, control, specifying, and recognition means to manage state changes of objects within a capturing range, ensuring that changes in light quantity or hue between captured images fall within a certain range, allowing for precise recognition without the need for high-performance devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a light source unit is flashed to associate position with captured image, then position association is improved, but luminance and color stability deteriorates
Solution Approach 1:
The system performs recognition processing on captured images before the light source flashes, or uses images captured during periods when the light source is not actively flashing for position association. This preliminary action prevents the harmful luminance changes from occurring during the critical recognition phase.
Solution Approach 2:
The system dynamically selects which captured images to use for recognition processing based on the flashing state of the light source. By adapting the selection criteria to the current lighting conditions, the system maintains recognition precision while accounting for inevitable luminance variations.
2Measurement precision
If recognition processing is performed on all captured images to raise precision, then recognition precision is improved, but processing load increases
Solution Approach 1:
Instead of performing recognition processing on all captured images, the system selectively processes only those images that meet specific criteria (e.g., images captured when the light source is not flashing, or images with acceptable luminance characteristics). This partial action approach achieves sufficient recognition precision without the excessive processing load of analyzing every captured image.
Solution Approach 2:
The system segments the captured images into different groups based on their suitability for recognition processing. By dividing the image set into categories (e.g., suitable images vs. images to be discarded), the system processes only the relevant subset, reducing overall processing load while maintaining precision.
3Measurement precision
If sensor output is used as trigger for imaging, then position association is improved, but clock synchronization becomes problematic
Solution Approach 1:
The system introduces an intermediary mechanism (such as a centralized timing controller or synchronization protocol) that coordinates between the sensor and imaging device clocks. This intermediary manages the timing relationship and compensates for clock differences, maintaining accurate position association without requiring perfect clock synchronization.
Data Source
AI summary
The object recognition system comprises: a detection unit for detecting a moving target object as an object to be recognized; an imaging unit for capturing a moving image of the target object; a control unit for controlling the state of objects, the state of which can be changed in a capturing area of the imaging unit, on the basis of the output of the detection unit such that a change in light quantity or hue between captured images due to the change in the state of the objects falls within a predetermined range; an identification unit for, upon detecting the change in the state of the objects included in the moving images, identifying a captured image to be recognized; and a recognition unit for recognizing the target object included in the identified captured image.