Machine Learning-based Automatic Optical Inspection System with Multimodal Optical Image Fusion Network

2021 ◽  
Vol 19 (10) ◽  
pp. 3503-3510
Author(s):  
Jong Hyuk Lee ◽  
Byeong Hak Kim ◽  
Min Young Kim
Keyword(s):  
Machine Learning ◽  
Image Fusion ◽  
Optical Image ◽  
Inspection System ◽  
Automatic Optical Inspection ◽  
Optical Inspection ◽  
Optical Inspection System

Development of an Automatic Optical Inspection System and its Application to Defect Examination

2013 ◽  
Vol 479-480 ◽  
pp. 636-640
Author(s):  
Jong Hann Jean ◽  
Chia Hong Chen ◽  
Tyng Bin Huang ◽  
Sheng Hong Tsai
Keyword(s):  
Inspection System ◽  
Large Object ◽  
Support Functions ◽  
Automatic Optical Inspection ◽  
Optical Inspection ◽  
Detection Tool ◽  
Measurement And Analysis ◽  
Processing Measurement ◽  
Inspection Machine ◽  
Optical Inspection System

In this paper, we have designed and integrated an automatic optical inspection system, emphasizing on software implementation of the image processing, measurement and analysis utilities. As for the hardware equipments, we design an LED illumination unit and the custom-tailored machinery. By comparing the support functions of several main import brands of the optical inspection machine, we propose an optical inspecting procedure. By using the Windows-based user interface, we implement nine inspecting software tools, namely, the average gray level tool, the thresholding tool, the positioning tool, the edge detection tool, the binary large object (BLOB) tool, the template building tool, the smart matching tool, the inspection sequence tool, and the platform operation tool. All these tools can be used in an inspection with single operation and can also be arranged in a proper sequence of operations to fulfill a complicated inspection procedure. We use several part sample images with defects provided by the supplier to verify our fulfilled system.

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