Today, you should know that data management and automation have evolved from old manual methods to AI technology solutions. As businesses endeavor to harness the power of big data, three pivotal methodologies emerge at the forefront: Data Extraction, Optical Character Recognition (OCR), and Intelligent Document Processing (IDP).
The difference between the three is that OCR is a technology that converts text in images into editable text, data extraction is the process of obtaining specific information from various sources, and IDP is based on OCR and AI technologies to automatically capture, understand, process and analyze document content, especially for semi-structured and unstructured data, thereby extracting useful information and converting it into actionable structured data. Furthermore, IDP can provide precise data support for large model training to enhance AI performance. Or integrating enterprise business systems, reducing repetitive tasks, and promoting workflow automation.
To better understand the difference among them, we will explore their definitions, working principles, differences, and application options in various industries.
1. OCR
1.1 What is OCR
OCR refers to a technology that recognizes text content from scanned documents, PDF documents, or images.
1.2 Traditional OCR
Traditional OCR technology primarily involves several steps to recognize text in images: preprocessing (denoising, skew correction, binarization), feature extraction, and classifier classification. This technology played a significant role in the early stages of digitalization, especially excelling in the recognition of scanned documents. However, with the rapid development of digitalization and increasingly complex scenarios, the recognition performance and accuracy of traditional OCR technology can no longer meet the needs of enterprises.
1.3 ComPDFKit OCR
ComPDFKit OCR function breaks through the limitation of traditional OCR that cannot guarantee accuracy and recognition performance in complex scenarios. ComPDFKit's AI-based OCR function supports intelligent text recognition in more than 70 languages( such as English, Korean, Japanese, and more) and different scenarios. Whether it is electronic documents, handwritten text, or text in natural scenes, it can be quickly recognized by AI technology with an accuracy rate of up to 95%.
Advantages
Compared with traditional OCR technology, ComPDFKit OCR function enriches application scenarios and improves recognition accuracy and completeness, thus helping enterprises improve document processing efficiency.
2. Data Extraction
2.1 What is Data Extraction
Data extraction refers to the process of collecting data (including text, tables, images, etc.) for further analysis and processing after pre-processing and recognition based on OCR technology from various different data sources.
2.2 Why Need Data Extraction?
Whether in the course of business operations or document collaboration processes, data processing is a very important component. It helps enterprises extract valuable insights from massive amounts of data and build databases to support decision-making and optimize operations, thereby enhancing corporate competitiveness.
2.3 ComPDFKit Data Extraction
PDF is a widely used document format, but it contains various page elements and styles, making the structuring process—which involves text extraction, image recognition, and table recognition—highly challenging. The ComPDFKit PDF data extraction feature effectively extracts all elements from PDF documents and uses document AI to understand the document structure and convert it into valuable structured data.
Benefits
The ComPDFKit data extraction feature employs AI-based OCR technology to effectively simplify the data extraction workflow. By merely uploading a PDF document and selecting the desired format (JSON, XML, CSV, and other formats), one can initiate the recognition and extraction of comprehensive PDF information, facilitating further processing in subsequent tasks.
Applications
ComPDFKit provides users with three data extraction solutions: API, SDK, and On-premise. No matter which solution you adopt, you can seamlessly integrate ComPDFKit's data extraction capabilities into your applications or systems, enhancing application functionality and improving user experience.
3. IDP
3.1 What is IDP
Intelligent Document Processing (IDP) refers to the process of automatically capturing, understanding, processing, and analyzing document content using technologies such as artificial intelligence, machine learning, computer vision, and natural language processing.
3.2 Why Need IDP
In the process of digital transformation, most enterprises face a large volume of unstructured data, making it difficult to enhance the level of automation. Although data extraction efficiency has improved, fully utilizing this vast amount of data for analysis to improve decision-making efficiency remains challenging. Moreover, traditional document processing workflows consume a lot of manpower and often lack accuracy, increasing the operational costs of enterprises.
These issues can be fundamentally resolved through a one-stop solution provided by IDP. IDP not only improves efficiency and accuracy but also helps enterprises easily achieve automated workflows, significantly reducing costs.
3.3 ComIDP Solution
ComIDP solution is an intelligent document processing solution that effectively aids enterprises in realizing data automation and enhancing document processing efficiency. It covers the entire document processing workflow, including document pre-processing, recognition, classification, data extraction, and data analysis, providing a basis for decision-making. It also offers out-of-the-box standardized models and customized AI to help enterprises quickly achieve digital transformation.
Benefits
ComIDP has patented-level layout analysis and table recognition features, suitable for various complex application scenarios, improving the efficiency of document processing workflows. Specifically, in terms of layout analysis, ComPDFKit Intelligent Document Processing can accurately detect page elements with 24 types of label, analyze the geometric layout, and restore the document's geometric structure to ensure data completeness. Using AI sorting algorithms to analyze logical layout, it restores the document's logical structure and retains the original reading order. It can also accurately recognize and interpret complex tables, including those with merged cells, nested layers, borderless formats, irregular column widths, and fuzzy borders.
Applications
ComIDP can be widely applied across various industries to achieve the structuring of a massive volume of documents, helping enterprises realize system automation, reduce costs, increase efficiency, and drive business growth. Additionally, ComIDP has important applications in AI large model training and digital management in the financial industry.
4. Comparison Table of Data Extraction, OCR, and IDP
In the previous sections, we explained the concepts of data extraction, OCR, and IDP in detail. By now, you should have a basic understanding of their differences. In this section, we will dive deeper into those differences.
From the table above, we can see that in the entire document processing workflow, OCR technology is used primarily for the preprocessing, recognition of the initial data source. On this basis, data extraction technology is employed to extract the required data and convert it into a format compatible with the target system, storing it in the target system for further analysis. IDP further builds upon this by understanding and analyzing the data, verifying it, and providing solutions for applying it in practical scenarios.
5. Sample Industry Applications: ComIDP & Data Extraction
In industry applications, how are IDP and data extraction used specifically? How to improve the efficiency of document collaboration in enterprises and help them achieve digital transformation? In this section, we will introduce you in detail through different examples.
5.1 ComIDP + Finance & Banking
In the financial industry, ComIDP can be integrated with existing financial systems to automatically extract and process uploaded forms, such as receipts and invoices. This facilitates the creation of financial reports and enables in-depth data analysis and insights, thereby aiding in the digitization of financial management.
In the banking industry, utilizing ComIDP solution can significantly accelerate the credit approval process. Through document format recognition, it automatically determines document types, intelligently categorizes, and archives various application materials submitted by customers. Subsequently, it intelligently extracts key information and employs automatic verification and cross-checking for document consistency, substantially improving review speed.
5.2 Data Extraction + Retail
In the retail industry, integrating ComPDFKit's data extraction capabilities into relevant application systems or programs can assist merchants in extracting the necessary data from various data sources, such as customer information forms and sales volume charts. This allows for the analysis of user behavior and preferences, thereby facilitating the formulation of future sales plans or product strategies.
6. FAQs
Q1: What's the difference between IDP and OCR?
A: IDP extracts data through OCR, it goes a step further. It combines multiple AI technologies to recognize and extract even the most difficult forms of data to automate. OCR can scan documents and convert them into machine-readable form, but can't understand data like IDP.
For example, OCR can recognize the numbers "1990" from a document, but it does not know that these numbers are part of a date of birth. IDP can understand the meaning behind this data well based on the context.
In short, IDP is easy to set up and deploy, can recognize and extract information in multiple formats, constantly learn, and improve over time.
Q2: Does IDP use OCR?
A: Yes, IDP is a one-stop solution for enterprise document processing based on OCR technology combined with a series of AI technologies such as ML and NLP.
Q3: What is the difference between OCR and text extraction?
A: OCR (Optical Character Recognition) and text extraction, though often confused, refer to distinct processes in document processing. OCR converts images of text into editable digital text, while text extraction identifies and retrieves specific information from text documents.
Q4: What’s the advantage of using IDP instead of OCR?
A: The main benefit of Intelligent Document Processing (IDP) over traditional OCR is its enhanced intelligence and automation. In short, IDP provides a more comprehensive, accurate, and automated solution, making it ideal for organizations seeking to improve efficiency and reduce manual document management.
Final Words
Now, you should understand the differences between OCR, data extraction, and IDP. ComPDFKit IDP (Intelligent Document Processing) is based on OCR technology and data extraction to provide businesses with a one-stop solution. This helps companies reduce repetitive tasks, automate document processing, and drive digital transformation.
So, if you're looking for a comprehensive automated document processing solution or if your document handling involves a certain level of complexity, choosing ComPDFKit IDP would be the best decision.
ComPDFKit has a professional development team and offers 24/5 online email and chat support, as well as one-on-one technical support and remote support services. Whenever you encounter an issue, you'll receive a prompt response. Contact us now to apply for customized ComIDP solution for your project.