Histogram Display for Image Capture Condition Verification
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Solution Overview
Problem
Existing image capture techniques struggle to efficiently optimize image capture conditions for capturing a workpiece with a complex three-dimensional shape, such as a vehicle body, as the brightness distribution changes significantly with each image capture, making it difficult to check binarized images for each of the approximately 1,000 images required in defect inspection.
Innovation Solution
A display body and data processing method that arranges and displays one-dimensional histograms for each captured image, using parameters like color coding or gradation to represent the frequency distribution of brightness, allowing for a comprehensive view of brightness changes across multiple images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If binarized images are checked for each captured image to optimize image capture conditions, then image quality can be improved, but the time required for verification increases significantly
Solution Approach 1:
The invention extracts only the essential brightness distribution information from each captured image by creating one-dimensional histograms, rather than processing the complete binarized images. This extraction allows verification of image quality through histogram analysis alone, significantly reducing the time required compared to checking each binarized image individually.
Solution Approach 2:
The invention transforms the two-dimensional binarized images into one-dimensional brightness distribution histograms. By changing the dimensionality from image pixels to brightness classes, the complex image verification problem is simplified into a statistical distribution analysis, enabling quick assessment of image quality without processing full images.
2Manufacturing precision
If exposure time is controlled based on substrate characteristics or reflectance, then image capture can be optimized for uniform objects, but the method cannot be applied to complex three-dimensional objects like vehicle bodies
Solution Approach 1:
The invention introduces dynamic adjustment of image capture conditions based on real-time histogram analysis of captured images. Instead of using fixed exposure times suitable only for uniform substrates, the system adapts exposure parameters dynamically according to the actual brightness distribution observed in each captured image, making it applicable to complex three-dimensional objects like vehicle bodies.
Solution Approach 2:
The invention implements a feedback mechanism where the brightness distribution histogram of each captured image is analyzed, and this information is fed back to adjust the image capture conditions. This closed-loop control enables the system to adapt to varying lighting conditions and object geometries, overcoming the limitation of static exposure time methods.
Data Source
AI summary
In a display body (6) (35), a plurality of one-dimensional histograms (5) are arranged and displayed, the one-dimensional histogram (5) being for each of a plurality of captured images obtained by capturing a workpiece (100) illuminated by an illumination device (1) with a camera (2) while moving at least one of the illumination device or the camera relative to the workpiece, and in the one-dimensional histogram (5), a frequency of a histogram indicating distribution of brightness of a captured image is one-dimensionally displayed in a direction of a class of the histogram by a parameter that can distinguishably represent a magnitude of the frequency.