Non-contact measurement & inspection


detection results than our competitors, we had defined a clear goal. For example, quality defects in food packaging were to be identified at a high production rate of up to two packs per second. This should enable inline rejection, which requires processing times of only a few milliseconds per image,” explains Emilio de la Red Bellvis, chief innovation officer at INNDEO. To achieve these goals, it was essential to automate the application end-to-end using machine vision.


DEFECT DETECTION VIA MACHINE VISION


So, what does the setup of the Thermoseal & Label Inspector look like in concrete terms? Cameras positioned at various inspection points take images of the objects. These are processed by the integrated machine vision software MVTec HALCON. HALCON is the comprehensive standard software for machine


vision, developed by MVTec Software GmbH, based in Munich.


There are different procedures for the various applications. For example, for sealed area inspection, HALCON determines the relevant area (Region of Interest/ROI) of the image for inspection based on various parameters. For this purpose, INNDEO uses high-resolution RGB vision technology for the simplest sealed area defects, such as a piece of ham, as its color is easily distinguishable in a transparent tray. In addition, the company uses hyperspectral vision technology for more complex defects. For example, melted ham fat in the same shade as the plastic of the tray or defects in opaque


or printed trays can be detected. Deep learning, which is a method in artificial intelligence (AI), is also used to detect certain defects. Through deep learning, the software attempts to simulate the behavior of the human brain and is able to interpret the images with a higher detection speed and efficiency than the human eye. The system is able to learn through a training phase, without the need for any additional programming by the user. This technology


Instrumentation Monthly March 2024


Continued on page 38... 37


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