Automation In Image Processing
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Automation in Image processing is an emerging technology which can prove very beneficial in the broad spectrum of fields, from quality control to asset management. Analyzing of an image or a video can done to deduce valuable information. Creating a model that helps in quality control, increases efficiency and speed of production by rejecting abnormal products automatically is vital.
Using the concept of image processing, we have invented our very own product. Using an image, it can analyse volume, weight, identification (barcode) of an item and then record it in seconds, in the database. Image processing can use in quality control by scanning the manufactured products and comparing them to a set of predefined characteristics.
A widely used technology for this is to use industrial image processing that based upon the use of special cameras or imaging systems installed within the production line. In this article, we propose a highly efficient model to automate central processing unit system production lines in an industry such that images of the production lines are scanned and any abnormalities in their assembly are pointed out by the model and information about this is transferred to the system administrator via a cyber-physical cloud system network. A machine learning–based approach is used for proper classification.
The results of analysis of image processing are more accurate as compared to when it is done manually.
The benefit of industrial image processing is in its non-destructive testing process, meaning that all of the objects that are tested will scan and evaluate without contact.