What are the pros and cons of using OCR vs. parsing for PDF data extraction?

2 Pros and cons of OCR

One of the main advantages of OCR is that it can handle any type of PDF, regardless of how it was created or encoded. OCR can also deal with different languages, fonts, and layouts, as long as the image quality is good enough. OCR can also preserve the original formatting and structure of the document, which can be important for some applications.

However, OCR also has some drawbacks. First, OCR is not always accurate, especially if the image quality is poor, the text is distorted, or the language is complex. OCR may introduce errors, miss characters, or misinterpret symbols. Second, OCR is computationally intensive and time-consuming, especially for large or complex PDFs. OCR may require a lot of resources and processing power, which can affect the performance and scalability of your data extraction process. Third, OCR may not be able to extract non-textual data, such as images, graphs, tables, or charts. OCR may ignore or misrepresent these elements, which can result in data loss or distortion.

3 What is parsing?

Parsing is a process that extracts data from structured or semi-structured PDFs by analyzing their internal structure and metadata. Parsing software reads the PDF file and identifies the elements and attributes that define the data, such as tags, fields, coordinates, or styles. Parsing can be useful for extracting data from native or digital PDFs, such as reports, catalogs, or ebooks. However, parsing also has some limitations and challenges.

4 Pros and cons of parsing

One of the main advantages of parsing is that it can extract data with high accuracy and reliability, as long as the PDF structure is consistent and well-defined. Parsing can also extract non-textual data, such as images, graphs, tables, or charts, by accessing their properties and metadata. Parsing can also be faster and more efficient than OCR, as it does not require image processing or recognition.

However, parsing also has some drawbacks. First, parsing is not suitable for unstructured or image-based PDFs, as it cannot access the data embedded in the images. Parsing may fail or return incomplete or irrelevant data for these types of PDFs. Second, parsing is dependent on the quality and standardization of the PDF structure and metadata. Parsing may encounter difficulties or errors if the PDF is poorly formatted, corrupted, encrypted, or protected. Third, parsing may not be able to preserve the original formatting and layout of the document, as it focuses on the data rather than the appearance. Parsing may alter or discard some elements or attributes that are not relevant for the data extraction.

5 How to choose between OCR and parsing?

Choosing between OCR and parsing for PDF data extraction is dependent on several factors, such as the type and quality of the PDF, the data you want to extract, the accuracy and speed required, and the resources and tools available. Generally, OCR should be used when dealing with scanned or image-based PDFs, if text is the primary data to be extracted, formatting and layout is important, and a good OCR software is present with enough processing power. Parsing should be used when dealing with native or digital PDFs, if structured or semi-structured data is needed, non-textual data needs to be extracted, and a good parsing software is available with a reliable PDF source. Additionally, other techniques such as manual data entry, web scraping, or data conversion may be necessary depending on your specific needs and goals.