Fast prototyping of a multi-camera inspection system ready to run AI algorithms

Fast prototyping of a multi-camera inspection system ready to run AI algorithms

Overview

Looking for an automated vision solution to capture high resolution images for the quality control in production. The images will be used to train a deep learning algorithm.

The customer is an industrial manufacturer of electronics. He is using a semi-automated and manual inspection flow and wants to upgrade to fully automated inspection to control the quality of the production.

Requirements

Our solution

Prototyping an Automated Optical Inspection system
Selection of a camera / lens system. The focus is on MIPI CSI cameras for easier integration later on.
The optical inspection system will use small low-cost cameras
MIPI CSI_2 camera modules are used in mobile phones but are now also available for industrial applications benefiting from the innovation in camera sensors for the mobile consumer market
Higher resolution is required to see the defects
An array of multiple cameras as camera resolutions for these kinds of cameras typically range from 5 to 18 Mpixel. Embedded software to produce a stitched image. The captured images will be used to train a deep learning algorithm to classify and detect the defects.
Higher resolution is required to see the defects
An array of multiple cameras as camera resolutions for these kinds of cameras typically range from 5 to 18 Mpixel. Embedded software to produce a stitched image. The captured images will be used to train a deep learning algorithm to classify and detect the defects.

Results:

A prototype of 12 cameras with supporting hardware and software is made to perform an automated image acquisition campaign. The prototype consists of an aluminium frame with built in 12 cameras, processing hardware and lighting. The software is able to do QR code reading, stitching & calibration of the camera images and has a management interface for an operator to capture images.
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