A comparitive study of Image Filters and Machine Learning for use in Machined Part Recognition

Abstract

The use of filters for image processing has long existed and is well established within industrial practice and in academia. The wide-spread adoption of machine learning into industrial spaces, however, has presented opportunities for the use of machine learning and artificial intelligence applications to be further developed and researched in relation to image processing. This paper aims to identify three of the main types of filters used in the machine learning process and to test their ability for target recognition of a basic/standard industry part.