Publication date: 01/10/2024
Optical Character Recognition (OCR) integration with Artificial Intelligence (AI) has significantly enhanced OCR capabilities. AI enables the OCR technology to play a pivotal role in the automation and compliance of workflows.
OCR technology is a way of the future, being introduced back in the late 1920s by physicist Emanuel Goldberg through his statistical machine. Emanuel Goldberg was able to extract ad words from the images. OCR technology has been used around the world by companies to eliminate manual processing of documents.
1. What is OCR?
It is a technology that extracts and reuses information from scanned documents. It is simple to convert images to text with the OCR technology compared to AI tools as the OCRs are specifically prepared for image to text conversion. You can convert the images captured by a camera. OCR software allows users to edit the original content of a scanned document.
Application of OCR: OCR technology is commonly used to convert images of hard documents to textual files. These documents can be resumes, legal contracts, historical documents, invoices, and more, into editable PDF files.
2. OCR and AI Data Extraction: How it Works?
Optical Character Recognition is the first step for the conversion process or extracting the text from the photos. To convert image to text in the modern digital world, the hybrid version of OCR and AI work in tandem. This is necessary for increasing the accuracy of the extraction process as it becomes difficult when low-resolution images are at the disposal. When a document or an image has been through an OCR process, then the AI models read out the OCR results and extract text from the images precisely.
Here describe, how OCR and AI work in tandem to make the extraction of text from images more reliable.
2.1. How Does OCR Work?
The OCR processing comprising of 6 different phases.
Image Acquisition
Pre-Processing
Character Segmentation
Feature Extraction
Character Classification
Post-Processing
The OCR tools convert images to text after the above-mentioned six steps.
2.2. How Does AI Data Extraction Work?
To extract data with the technology, a text layer is required to structure the data. Therefore, the files uploaded to a system first need to be processed by the OCR system.
So the AI data integration needs the following steps:
Text Layer Requirement: AI systems require a text layer to extract and convert images to text data.
OCR Processing: The text layers are extracted with the OCR technology and it is necessary for implementing the AI extraction.
Accepted Formats: OCR technologies can capture the data from PDF, JPG, and DOCX files. So normally AI technologies extract data from these data formats.
Data Extraction: The data extraction is done by the deep learning-based OCR technology to convert images to text with the AI-embedded technology in the online tool.
Data Export: AI technologies assist in extracting data to CSV files or integrating it into software like ERP or CRM systems.
AI-based automated data extraction is faster, more accurate, and easier to use as compared to manual OCR extraction.
3. Comparison of OCR and AI Data Extraction:
The comparison between the OCR and AI extraction is given below in the table. Both processes have their pros and cons, but the hybrid approach is one of the more advanced approaches regarding data extraction. You can convert image to text with the hybrid approach more accurately combining the strengths of AI and OCR technology.
Method | Advantages | Disadvantages |
Optical Character Recognition (OCR) | May have accuracy issues with complex documents or poor-quality images | |
AI Data Extraction/Intelligent Document Processing | Highly accurate, can handle complex documents, automates many tasks | Can be expensive to implement, requires specialized expertise |
Hybrid Approach | Combines the strengths of both OCR and AI, offering a balance of speed and accuracy | May be more complex to implement and manage |
4. FAQs:
4.1. How OCR Has Transformed Throughout History?
The OCR technology has changed throughout history from its birth in 1920s by the Emanuel Goldberg to the present. Now the OCR services are integrated with Artificial Intelligence (AI) technology for better speed and accuracy of text extraction from images.
4.2. Why Your Business Needs OCR and AI Data Extraction Technology?
The dynamics of an image to text conversion are changing and you need efficient and accurate document processing capabilities. So businesses are turning towards OCR and AI integration due to the following reasons.
1. Accuracy
2. Less Manual Data Handling
3. Scalability and Flexibility
4. Increased Compliance and Security
4.3. Why are Businesses Embracing AI-powered OCR Technology?
By embracing AI-powered OCR to extract text from images, a business can enhance its operational efficiency, and improve data accuracy. A business can pave the way for innovative document processing by hybrid operational efficiency. Employees can focus on strategic tasks rather than operations issues and problems.
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