Use LLMs and OCR to Extract Data from Images

Abstract

Using images as data sources is becoming increasingly popular among organizations today; however, extracting structured pieces of information from images remains a difficult challenge. Optical Character Recognition (OCR) technology has been widely used for many years to extract text from images and photos, but it does not take into account the context, structure, and relationships of the extracted data. The integration of OCR with Large Language Models (LLMs) enables businesses to go beyond text extraction, to the next level where words can be understood, categorized, organized, and data put in context.

During the talk, I will explain how this combination of technologies can be used to change unstructured image data into useful information by providing actionable insights. Advance with us as we take you through the deficiencies in the conventional OCR, how it is continually improved and the fundamentals of low-quality image, handwriting, and multi-language extraction. The session will also discuss how LLMs can support OCR by helping endow meaning for identifiers and entities to define relations that help primary processing.