Spark Plug Identification and Classification
Cognex Deep Learning location and classification tools identify, count, and classify parts based on their appearance
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Powered by In-Sight ViDi Deep Learning-Based Vision Software
A breakthrough in complex inspection, part location, classification, and OCR
For certain identification, counting, and classification applications, manufacturers must rely upon visual inspection when their environments do not support barcode reading technology. Slight variations in appearance can cause complications for an automated inspection system. This is the case for spark plugs, which arrive for pre-assembly on differently colored trays. The inspection system must successfully identify, count, and classify differently colored spark plugs while ignoring the background color of their trays. This information is then communicated to a vision-guided robot for assembly.
Cognex Deep Learning generalizes the distinguishing features of a spark plug based on its size, shape, and surface features. With the location tool, an engineer fixtures tray images, teaching the software to identify and count individual spark plugs. The classification tool uses the deep learning-based model to classify the spark plugs by the feature germane to the robot - its color.
