Analysis of Image Processing techniques for Machinery Part detection :A Review

Detecting an object is an acute job in the automation industry, and when it comes to the machinery parts then one has to know when an object has reached at a expected location. In the automation industry , the objects or the parts of the objects are detected based on the object passing by on a conveyor, the closure of a door, or the arrival of a carrier at a stop. Such machine part recognition and defect detection involves the specific models or shapes of machine parts. These are then generated as dataset that are created from the good machine parts. In turn such model/ shapes are used during the similarity matching process. Assembly line automation are significant to handle the day by day demands of latest technology machines that can utilize the image processing techniques Artificial neural networks ,machine learning etc., which are used in industry and society. The detection and identification of defects in these machinery parts helps in smooth manufacturing process if they are detected at the a very early stage and these in turn saves production cost and time. This paper is a review of such techniques that are used to detect machinery parts and then the obtained image is processed by different image processing methods.