What is OCR?
What is OCR? Also known as Optical Character Recognition
OCR (optical character recognition)
is a popular technology that converts any text or information stored in digital documents into computerizable data. All kinds of documents and paper documents are converted into files that can be read by computers suitable for data processing.
First conceptualized in the early 20th century when reading machines for the blind were being developed, commercial implementation of OCR began in the 1990s. They have widely used the technology to digitize newspapers and legal documents, especially as their use of databases increased in the 1990s. Today, OCR is available online and with APIs that integrate seamlessly with applications.
Besides, over the years businesses have widely used OCR tools to extract text from images, extract text from images, convert PDF to Excel, extract text from these files. They also used it to extract tables from PDF. In fact, the new generation of OCR software utilizes artificial intelligence applications to achieve more advanced levels of recognition.
How do OCR Systems Work?
Basically, after starting with a short definition of what OCR is, let’s look at its stages. This process usually involves the following stages:
- Pre-processing of images
- Recognition of characters
- Post-processing of output
First, image preprocessing minimizes the impact of constraints in images (blurs, curvatures, points, colors) to increase the likelihood of accurate recognition of data. OCR software uses various techniques to improve image quality, alignment, clarity and orientation. Images like this produce better OCR output.
Now, let’s move on to character recognition. It uses various methods to divide the image into segments or regions and recognize the characters within them. These methods range from pixel-by-pixel comparison to the use of artificial intelligence components to recognize entire lines of text at a time.
Finally, the step of post-processing the output. It includes techniques and algorithms to improve the accuracy of extracted data by first detecting and then correcting errors. This stage involves comparing the extracted text/data with a standard dictionary or vocabulary and taking into account grammatical considerations.
Uses of OCR
First, let’s recall the basic function answer to the question What is OCR? Businesses primarily used it for documents that were clearly physical or scanned. It was then used to convert data into machine-readable formats suitable for word processors such as Word, Excel, Docs or Spreadsheets. Most online converters use OCR in the background to convert inoperable file formats (e.g. TIFF, PNG or PDF) into editable output. However, besides these well-known examples, it is also widely used for the following purposes:
- Data entry automation
- Indexing documents, web pages and information for search engines
- Driver’s license and license plate recognition
- ID, passport reading
- Assisting the visually impaired through text-to-speech services
- Insurance claims processing
- Invoice
- Counter
- Form
- Multilingual translation services
- Verification and validation of legal documents
However, in recent years OCR applications have also emerged to read only certain types of documents. These include invoices, receipts, passports, data capture on IDs, etc. diversity. They are all based on similar optical character recognition features. Also, contrary to popular belief, handwriting recognition technology is known as ICR, not OCR.
Advantages of OCR
Here are some of the key benefits that businesses can achieve by automating their internal workflows with optical character recognition:
- Eliminate inefficient, slow and error-prone manual processes
- Cost savings through faster data processing and more efficient resource utilization
- Replacing days of manual processes with automated workflows completed in minutes
- Avoiding physical infrastructure to store and support documents
- Ensuring efficient data storage and data security
- High level of accuracy
- Redirecting internal teams from trivial/repetitive tasks to more important value-creating tasks
Why Papirus AI?
Now, we have detailed information about What is OCR. And where does Papyrus Digital fit in? Modern OCR software that leverages artificial intelligence features. It allows users to create custom models for any text recognition or data extraction use case.
It is also far ahead of other OCR software in cost savings and data accuracy. Unique benefits that put Papirus AI ahead of the competition:
A Service, Not Just a Packaged Product – The AI-powered platform does not require an in-house team of developers. All development is by Papirus AI teams. Moreover, thanks to its ready-made API, it can be easily integrated with most CRM, ERP or RPA software.
Only Requested Data – While most OCR software simply extracts the raw data from documents, Papirus AI extracts only the relevant data. As a result, it automatically writes them into the relevant fields in a structured way.
Any Document Type – OCR (optical character recognition) products are very strict about the types of documents they can work with. It is extremely important that these products offer flexibility to suit every need. But Papyrus Digital does not contain such constraints. Processes all non-structural, semi-structural and structural document types required to meet the specific needs of your business.
Image-based Constraints – Utilizes Computer Vision techniques to overcome image quality problems that greatly affect data recognition. Recognizes text images in multiple languages, low resolution images. It also captures different fonts and images of varying sizes. However, it is successful in images with shaded texts, italicized texts, unstructured texts. It recognizes image noise, blurred images and more.
Endless customization – Capture as many text/data fields as you want with Papirus AI. It can even create custom validation rules that only work for specific use cases. In particular, it is in no way tied to the standard document template.
Table/Lie Item Extraction – With its highly capable algorithms, you can also capture data from tables or rows.
