Testing device, assembly device and testing procedure

The test device uses machine learning to create frequency distributions of light density values for precise component identification on circuit boards, addressing misidentification issues by focusing on bins with significant frequency differences.

DE112022007397T5Pending Publication Date: 2025-04-03FUJI CORP
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Patent Information

Application Number
DE112022007397
Authority / Receiving Office
DE · DE
Patent Type
Applications
Current Assignee / Owner
Filing Date
2022-06-20
Publication Date
2025-04-03

AI Technical Summary

Technical Problem

Existing test devices for determining the presence or absence of components on circuit boards are prone to incorrect determinations due to variations in luminance and light reflection, leading to potential misidentification of components.

Method used

A test device utilizing machine learning to create frequency distributions of light density values for each pixel, setting specific bins as determination targets, and comparing frequencies within these bins to accurately determine the presence or absence of components.

Benefits of technology

This method significantly reduces the influence of luminance variations, allowing for precise determination of component presence or absence by focusing on bins with the greatest frequency differences, thereby minimizing incorrect determinations.

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Abstract

A test device configured to check for the presence or absence of an object by means of image processing comprises a setting section configured to create or capture a frequency distribution obtained by aggregating a frequency of a feature value in each pixel of an image for each presence or absence of an object using machine learning, with the image associated with the presence or absence of the object, and to set a portion of each bin of the frequency distribution as a target bin, and a targeting section configured to capture a target image of the test.to compare a frequency of a feature value belonging to the target bin within the feature values ​​in each pixel of the target image with a frequency belonging to the target bin of the frequency distribution for each presence or absence of an object, and to determine the presence or absence of an object in the target image.
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