Extracting text from a PDF might seem like a simple task—until you try copying and pasting and end up with a jumbled mess. Whether you're dealing with scanned documents, complex layouts, or encoded text, PDF text extraction requires the right tools and techniques to get clean, usable content. In this blog, we’ll break down the basics of PDF text extraction, explore different methods, and help you choose the best approach for your needs.

Common scenarios for why text needs to be extracted from a PDF are:

To index the text
To analyze the text
- with or without information about the positioning/style of the text

The main elements of PDF text extraction include:

Text Extraction Techniques:
- Unicode Text Extraction: PDFs can store text using Unicode encoding, which allows for extracting text with proper character encoding.
- OCR (Optical Character Recognition): In cases where the PDF contains scanned images or non-selectable text, OCR technology may be used to recognize and extract text from images.
Libraries and tools:
- Various tools and libraries provide APIs (Application Programming Interfaces) for programmatically extracting text from PDFs.
- Examples of these tools include Adobe Acrobat, PDFBox, PyPDF2, pdfplumber (for Python), iText (Java), and our PDF SDK, Adobe PDF Library.
Use Cases:
- Content Analysis: Text extraction is often used for content analysis, allowing applications to analyze and process the textual information within PDF documents.
- Data Extraction: Extracting structured data from PDFs, such as tables or form data, is a common use case.
- Searchable Archives: Making the content of PDFs searchable by extracting text allows users to find specific information within large collections of documents.
Challenges:
- Text Layout: PDFs can store text in a way that reflects the visual layout of the document, which can pose challenges in maintaining the original formatting during extraction.
- Image-based Text: Some PDFs may contain text as images, requiring OCR for accurate text extraction.
- Encrypted PDFs: Encrypted PDFs may require decryption before text extraction can take place.
Programming Interfaces:
- Most programming languages have libraries or APIs that facilitate PDF text extraction. These libraries provide methods to parse the PDF structure and extract text content from the PDF.

Read Cracking the Code: PDF Text Extraction

PDF Text Extraction Using Adobe PDF Library

The Adobe PDF Library SDK can handle nearly any use case for PDF text extraction, including:

Fillable Forms

Extract text from the AcroForm fields in a PDF document. This is useful for those who work with fillable forms in PDFs and need to extract the text within the AcroForms as a .JSON file to use in a text editor or web browser.

Searching for Patterns

Search for patterns within the text of a document, such as phone numbers, using simple overarching commands and extract the data into a .TXT file. For example, phone numbers in the U.S. are set up ###-###-####, but that format varies worldwide. This sample makes it easy to extract any phone number by simply using ‘PHONE_PATTERN’ in the code instead of ((1-)?(\()?\d{3}(\))?(\s)?(-)?\d{3}-\d{4})

You can also search for Unicode characters such as Chinese, Japanese, and Korean (CJK). With more than 1.5 billion people speaking those languages (and growing), organizations must be able to extract millions of different types of characters correctly.

Extract Text by Regions

Extracting text by region has to do with extracting text from a specific region of a page in a PDF document, which then saves the extracted text to a .TXT file. For example, companies who have thousands of invoices with the same number format that need those numbers extracted from that specific region on the PDF, or when the IRS must pull social security numbers from that section of their 1044s, can use APDFL to accomplish that task.

Extract Text from Multiple Regions

This processes PDF files in a folder and extracts text from multiple specific regions of its pages and saves the text to a .CSV file. For example, this command can create a single file with all the invoice numbers, dates, order numbers, customer IDs, and total from the invoices in the folder, so you have all the data you need in one view.

Consolidating Annotations

PDFs can contain thousands of annotations and with text extraction, you can pull that information out and save it to a separate text file (in .JSON). For example, contract negotiations may include comments and questions that have been accepted or rejected, and this function can extract that data.

Style Preservation

If you are looking to extract text while preserving the original style of the document, you can extract all text from the PDF along with information about the text (in a .JSON file) such as its style, color, and font size for style preservation.

Need to extract images from PDFs? We can do that too!

To start editing PDFs, sign up for a free trial of ourAdobe PDF Library SDK and start on your proof of concept today!