Abstract
Latency and image blurring are major limitations of machine vision processes, which often require every target object to pause for a moment for capturing and processing a still image. When a large number of objects are to be inspected, such a stop-and-go approach may significantly degrade the test efficiency due to a long inspection time. This paper investigates the performance and error analysis of dynamic imaging approach where the image is captured and processed on-the-fly while the target object is still moving. Taking images of a moving object can substantially enhance the inspection speed but intensifies latency and image blurring. To overcome these issues, firstly, we implement the controlled trigger, i.e., to operate the machine vision in synchrony with the position sensing while the target object is moving. Then, we attempt to restore the blurred pixel data through advanced image restoration techniques. The main ideas are applied to a semiconductor test process called the probe card analysis and its performance is experimentally verified.
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