Named entity extraction from images using natural language processing pipelines

Named entity extraction is the process of extracting a specific entity or a piece of information from a bunch of text or an image where a lot of text has been mentioned. For example, identifying the name of a candidate from a resume or picking out the name of a cereal brand from its box. Technologies like optical character recognition and named entity recognition have been widely used in their respective fields of applications. Both of these technologies can be combined to form a pipeline in which we can extract a particular word using named entity recognition from the output digitized text from the optical character recognition system. The combined models and their use cases will be discussed in this paper. The implementation on the drug strips and their various applications both in consumer as well as retailer sub sections will be mentioned. Models and their improvements with recent and concurrent published papers will be discussed.