Packaging Optical Character Recognition
Cognex's deep learning OCR tool is able to detect and read the plain text in date/lot codes, verifying that their chains of numbers and letters are correct even when they are badly deformed, skewed, or—in the case of metal surfaces—poorly etched. The tool minimizes training because it leverages a pre-trained font library.
Training is limited to specific application requirements to recognize surface details or retrain on missed characters. All of these advantages help ease and speed implementation and contribute to successful OCR and OCV application results without the involvement of a vision expert.
Packaging Assembly Verification
A deep learning-based system is ideal to locate and verify that individual items are present and correct, arranged in the proper configuration, and match their external packaging. It generalizes each item’s distinguishable characteristics based on size, shape, colour, and surface features.
The Cognex Deep Learning software can be trained quickly to build an entire database of items. Then, the inspection can proceed by region, whether by quadrant or line-by-line, to verify that the package has been assembled correctly.
Categorization is important yet remains out of reach for traditional machine vision. Luckily, Cognex's deep learning classification tool can easily be combined with traditional location and counting machine vision tools, or with deep learning-based location and counting tools if the kitting inspection deals with variable product types and requires artificial intelligence to distinguish the generalizing features of these types.
This content was sponsored by Cognex.