Introduction
The demand for extracting text from PDFs has exponentially increased over recent years. Owing to the technological advancements in OCR (optical character recognition) technology, text extraction has become increasingly accurate, efficient, faster as well as effective. With numerous applications in the real world, it is important to understand the process of text extraction from PDFs.
Use Cases of OCR
The various real-life applications and use cases for extracting text from PDFs include the following:
- Retail sector – used for inventory management
- Transportation industry – used for automated toll collection as well as traffic management
- Education sector – used in digital textbooks for better understanding and learning experience
Key Advantages
The key advantages of extracting text from PDFs using OCR technology are:Â
- Enhanced Accuracy and Versatility – Text extraction from PDFs has become extremely easier, faster, accurate, efficient as well as effective as a result of the improvements in the OCR technology. Additionally, texts from PDFs including handwritten text can also be extracted efficiently.
- Faster Processing Speeds – With the advancement and employment of optimized algorithms and parallel processing, the time taken to extract data from a PDF has significantly improved over the years.
- Intelligent Document Processing (IDP) Solutions – With the onset of accurate data extraction and classification into relevant data, numerous IDP solutions are created using advanced NLP techniques and ML algorithms.
- Continuous Improvement through Machine Learning – With the introduction of GenAI in OCR technology, extracting texts from PDFs has been significantly improved as a result of continuous improvement through machine learning.
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A Comprehensive Guide to Using OCR
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