ABSTRACT
Our Project discusses an E-quality learning system developed to automatically
measure and monitor the surface roughness of products by utilizing vision
technology. Several methods have been developed to measure surface
roughness in industry. These methods utilize a contact-based approach to
perform the necessary measurements. Our system is developed based on a noncontact
method that uses a smart machine vision camera and Lab VIEW-based
programming. The method for determining the roughness is based on the
correlation of optical roughness parameters and the average surface roughness.
After the surface roughness monitoring system has been built, it can be applied
as an automated quality control system used for educational purposes.
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