Except for the author, PDFs are rarely modifiable by default. Most users lack access to the tools necessary to alter PDF files. Along with this, the issue of embedded typefaces is another frequent concern when working with PDFs. A PDF’s text may not always be selectable. The issue is that the PDF could not have originally been text but rather a snapshot of a real page that was then converted to a PDF. The similar issue arises when attempting to extract data from photographs since text inside them cannot be selected.
So how does one approach these problems?
We will go through how to extract text from scanned and non-scanned PDFs and photos in this post.
Let’s begin and explain now.
Table of Contents
What is Data Extraction?
Data extraction is the process of using software to turn unstructured data into understandable information that can then be processed further by people. The most popular data types that can be retrieved from scanned documents are listed below.
- Text Data
Text extraction from scanned documents is the most popular and crucial data extraction operation. Although it may appear simple, this technique is really highly challenging since scanned papers are frequently presented as pictures. Additionally, the types of text have a significant impact on the extraction techniques. The capacity to extract sparse text from poorly scanned documents or from handwritten letters with wildly different styles is equally significant, even though content is often available in dense printed formats. Programs will be able to transform photographs to machine-encoded text using such a procedure, which will then allow us to further arrange the images from unstructured data (without specific formatting) into structured data for additional analysis.
- Tables
The most common method for storing data is in tabular forms since it is simple to understand by human eyes. Beyond character detection, technology is needed to properly extract tables from scanned documents. This information must first be converted into structured data for further processing, which needs the recognition of lines and other visual aspects. To accomplish high precision table extraction, computer vision techniques—which are covered in more detail in the next sections—are actively utilised.
Extract text from PDF and Images with Optical Character Recognition(OCR)
Whether a document is constituted of text or graphics, OCR technology may be used to scan it for text. To determine if any given portion of a document may be an alphabet, number, or character, it employs pattern recognition algorithms. Once the picture has been recognised, the OCR extractor either turns it to text on the document itself or removes it from the document and places it in a different context. An OCR extractor is a crucial piece of technology for many different industries and uses.
Why use an OCR extractor?
All data extraction from scanned documents must be done manually in the absence of OCR extractors. Before you may evaluate your data if it is only available in PDF format, you must duplicate it on an excel sheet. As you can expect, manual data input takes a lot of time and is prone to a variety of mistakes. Senior management frequently lacks the time to handle manual data, so they must either employ someone to do it or outsource the entire procedure. In addition, real-time data tracking is not possible.
The OCR extractor offers a comprehensive answer to each of these problems. In a couple of seconds, a skilled OCR extractor can extract all the necessary data.
Challenges in extracting data from PDF documents
Even if you have an OCR extractor, they frequently have certain restrictions. Here are just a few obstacles you could run into while using an OCR extractor:-
- The document was never text
The OCR extractor will probably have an easy work on its hands if the document being scanned was originally created as a text document since the characters will be readable. However, most OCR extractor programmes would struggle to extract data if the document was an image that was converted to a PDF and never had any text.
- The document contains tables
Not all OCR extractor will perform well if you are extracting data from a PDF. FacePdf naturally treats text that is horizontally oriented as a line. As a result, it may have a lot of trouble understanding tables, which are collections of separate texts. This may become even more challenging if the document has nested tables, or tables inside of tables.
At FacePdf, we created a unique free tool just to get over this restriction. You may extract tables and photos from any PDF document, scanned or not, with FacePdf free table extractor application. Take a look for yourself.
- Image clarity
The performance of the OCR extractor is significantly influenced by the image’s clarity. Only an OCR extractor that has received thorough training on a wide variety of image types will be able to extract text from pictures shot in various lighting conditions.
How does OCR work?
Letters, characters, and symbols are represented in documents by patterns of light and dark that may be recognised using optical character recognition (OCR). Modern intelligent OCR technology is capable of identifying many typefaces in documents, handwritten notes, and cursive writings, whereas early OCR systems were only intended to deal with a small number of fonts.
Users must first upload scanned copies of their papers onto the platforms in order for OCR technology to function. Character by character, the technology reads through the whole document to identify sentences and line items. Following data reading using OCR algorithms, documents are extracted and converted into editable text. Users have the option to export their papers in a variety of file formats, including PDF, JSON, CSV, and Excel spreadsheets.
Conclusion
Both businesses and individual users need an OCR extractor that solves these issues and enables them to extract data more quickly and accurately. The free OCR scanner from FacePdf is an efficient tool for extracting data from any document. Do it right now to judge for yourself!
