Optical character recognition (OCR) technology turns the picture into text so people can edit them. This way, OCR can get useful data from a picture.
This technology is used in different industries to change lots of biological information into digital formats. Because it has many benefits over paper documents, it has become the normal way businesses around the world work.
OCR technology turns scanned documents into searchable, editable digital files. It takes text from images or scanned documents using pattern matching algorithms. OCR technology keeps improving for accurate, effective text recognition. There are even OCR tools for receipts that can simplify collecting data for expenses, removing the need for expensive manual data entry.
This article will explain what OCR is, why it’s useful, and how it works. Let’s start by describing OCR in more detail.
OCR is basically a text recognition technology, as I said at the start. It can help get text from different sources, including photos, newspapers, and handwritten documents that have been digitized. OCR processes documents to get good conversion results.
This includes pre-processing, conversion, and post-processing steps. Techniques like character segmentation make sure the text matches the image. Many different tools and software programs use OCR.
Users of these tools can get text from images. OCR tools can also change data from images into formats like Word files and PDFs.
OCR technology turns a picture of a document into text a computer can read. It does this by looking at the shapes, patterns, and lines in the image. Usually, the process has several steps:
- Digitize Image
The document is either scanned or photographed to make a digital image.
The image is improved to make the text higher quality and more readable.
- Text detection
OCR algorithms find the text areas in the picture.
- Character recognition
The recognized text characters are analyzed and turned into digital text.
The recognized text is further processed to fix mistakes and increase accuracy.
The final product is a searchable, editable digital document.
Now let’s talk about how OCR can help with document digitization. Document digitization means turning paper documents into searchable electronic versions. This can be done using OCR tools to change images of these documents into editable text.
OCR can find all the characters in a document, including unique symbols, graphs, and tables. These characters show up in the image in the same place and format, according to the results.
Digital documents are easier to access than physical ones since they can be searched using a search bar. OCR is used in document digitization because this can only be done if the documents are in an editable format.
An example of such OCR software or equipment is Image to Text, a free online text extraction tool. It can help digitize documents very well. It offers various optimization options. For example, you can extract files from your computer rather than upload them. You can also extract text from an image URL.
Using OCR for document digitization helps protect data from physical damage. For example, paper documents can be physically harmed in different ways, like from danger (fire, theft, etc.). Digital copies don’t have this problem.
Also, some mistakes during digitization could lead to losing key data. For instance, someone might miss a section of the document when manually extracting text and leave it out of the final product. This could taint your file. OCR can help avoid this because it thoroughly checks the document and makes accurate results.
OCR tools secure data, review results, adjust extraction, and put preventative measures in place.
OCR technology is used in many industries around the world. OCR is mainly used to get text from non-editable files, like images. You could do this by manually typing out the information after looking at the picture. But this method might not be as efficient due to issues with time, accuracy, and cost.
Instead, OCR can do this job with the highest efficiency and accuracy. Here are some benefits of OCR over manual text extraction:
- Using OCR, text extraction only takes a few minutes. OCR software can quickly turn lots of images into text.
- Most online OCR tools are free or just a small monthly fee to subscribe.
- OCR allows focus on other business aspects instead of digitizing old documents.
- OCR produces very accurate results. According to one source, good OCR software can get text from images with 98-99% accuracy.
- Improves workflow efficiency and productivity. OCR streamlines accessing information, eliminating manual handling and data entry.
- Improves searchability. You can search for specific words or phrases in digitized docs with OCR.
- Saves money on paper, printing, and storage. Digitizing docs reduces waste and supports the environment.
- Reduces human error that happens with manual data entry. Automated text recognition improves accuracy.
- Makes collaborating on digital files simple by enabling multiple users to access and edit the same file.
OCR technology is used in a variety of fields and situations. Here are a few instances:
- Archiving and retrieval of documents
OCR makes it easier to archive and find documents quickly using search.
- Invoice Processing
OCR automatically gets invoice data like items, vendor info, and numbers. Reduces manual data entry for accounts payable.
- Data Input and Extraction
OCR can automate data entry from forms, surveys, etc. Saves time and resources for faster data processing.
- ID verification and authentication
OCR extracts data from IDs for swift, accurate verification in sectors like government.
Optical character recognition (OCR) technology extracts text from images and non-editable files to convert them into searchable, editable digital documents. OCR delivers major efficiency benefits by automating digitization, allowing accurate data extraction, and improving information access and productivity. It reduces costs, errors, and environmental impact while securing digital files. OCR tools are easy to implement and widely used across industries to digitize documents more efficiently than manual data entry. Overall, OCR provides key advantages for document digitization and business productivity.