Imaging Consistency Detection for Industrial Vision Accuracy
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Solution Overview
Problem
Industrial image processing systems face challenges in maintaining imaging consistency due to factors like blocked light sources and optical path misalignment, leading to inconsistent imaging and reduced accuracy in product detection.
Innovation Solution
A method and device for detecting imaging consistency by determining target regions in images, obtaining first image information, and checking against preset conditions for brightness, clarity, and location to ensure consistency, with optional use of segmenting and locating methods for accurate region identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing technology is applied in industrial manufacturing, then detection accuracy is improved, but imaging consistency deteriorates due to environmental factors like blocked light sources and optical path misalignment
Solution Approach 1:
The patent applies preliminary action by performing imaging consistency detection before actual product detection. The system acquires images of standard objects (like coins or plugs) under the same imaging conditions, extracts feature information, and compares it with reference data to determine whether the imaging system meets detection requirements. This preliminary check ensures that only when imaging consistency is verified does the system proceed to actual product detection, thereby preventing environmental factors from compromising detection accuracy.
2Measurement precision
If the system detects all regions in the image, then comprehensive detection is achieved, but detection efficiency decreases due to processing large amounts of data
Solution Approach 1:
The patent applies segmentation by dividing the image into multiple regions of interest (ROIs) based on predefined criteria. Instead of processing the entire image, the system identifies and extracts specific regions containing potential defects or features of interest. This segmentation approach reduces the amount of data requiring detailed analysis while maintaining comprehensive detection coverage, thereby improving detection efficiency without sacrificing thoroughness.
Solution Approach 2:
The patent applies local quality by applying different processing strategies to different regions of the image. High-priority regions with potential defects receive detailed analysis with strict detection criteria, while low-priority regions undergo simpler processing. This localized approach optimizes resource allocation, ensuring that detection efforts are concentrated where they are most needed, thus balancing comprehensiveness with efficiency.
3Measurement precision
If strict detection criteria are applied, then detection accuracy is improved, but false rejection rate increases leading to loss of good products
Solution Approach 1:
The patent applies feedback by implementing a multi-stage detection process with iterative refinement. The system first performs preliminary screening with moderate criteria, then applies stricter criteria only to suspicious regions identified in the first stage. Detection results are fed back through comparison with reference data from standard objects, allowing the system to adjust its judgment. This feedback mechanism reduces false rejections by providing multiple verification opportunities while maintaining high detection accuracy through progressive filtering.
Data Source
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AI summary
An embodiment of this application discloses a method and device for detecting imaging consistency of a system, and a computer storage medium. The method includes: determining a target region in an image acquired by the system, where the target region is a partial region that includes a target object in the image acquired by the system; obtaining first image information of the target region; and detecting the imaging consistency of the system based on the first image information. By obtaining the first image information of the target region in the image acquired by the system and determining the imaging consistency of the system based on the first image information, this application can effectively detect the imaging consistency of the system and improve accuracy of product detection.