Optical character recognition (OCR) is a process — usually provided by an OCR SDK — that transforms characters in photographs into text documents by removing the need for manual input.
It can read characters from identification cards, driver’s licenses, vehicle titles, receipts, common tables, and standard text.
OCR offers real-time access to and use of APIs. We use it to acquire the inference result, considerably enhancing company productivity.
This post will look at OCR SDK, how it works, and how you can use OCR to automate your data extraction processes and save time.
So let’s get into it.
What Is OCR Technology?
OCR technology is a process that breaks up, scans, and evaluates the image structure of a page separated into chunks of tables or text lines. These lines are then broken into words and, finally, into characters.
Once the OCR technology has identified certain characters, it compares them to a set of pattern images. It then develops several hypotheses to determine the characters’ nature.
Using these proposed theories, an OCI API investigates several ways of dividing lines into words and characters. Therefore, the API displays the interpreted text once it has correctly determined the identity of the scanned symbol.
Various industrial verticals use OCR technology to scan, save, process, and exchange documents, including:
- Banks use OCR algorithms to capture and extract data, archive client-related documents and improve accessibility to digital content.
- Loan officers use OCR to detect fraud and forgery cases.
How Accurate Is OCR Technology?
OCR technology is widely acknowledged to be 98 to 99 percent accurate in reading and deciphering information from papers. This means that for a 1,000-word document, the program can reliably read and record up to 980 or 990 words.
Let’s understand one thing about intelligent data entry. First, the high field-level accuracy rating of OCR technology enables users to achieve total automation.
The technology necessitates little to no manual inspection after data is input by software algorithms.
You can measure the accuracy of an OCR SDK by taking the output of an OCR image run and comparing it against the original version of the exact text.
Although the SDK is highly accurate if the image run displays almost no character or word-level errors. However, the SDK isn’t precise if the image run shows an excessive number of errors.
What Is OCR SDK?
The OCR Software Development Kit (OCR SDK) is a practical and reliable document processing service that converts printed or handwritten documents or digital images into machine-readable text.
First, it enhances data processing, increases data extraction accuracy, converts documents into readable formats, and utilizes textual information from images, screenshots, PDFs, scans, and documents.
Second, OCR SDK improves workflow automation, allows excellent text recognition, and reduces manual data entry, often error-prone, costly, and time-consuming.
Third, it frees businesses from worrying about information processing and enables them to use straightforward, thoroughly documented APIs for all their OCR requirements.
What Are The Essential Features of OCR SDK?
An OCR SDK offers detailed location and format information, including font names, font sizes, line widths, and more, in addition to essential OCR findings.
The SDK’s PDF output, where documents can be authored in plaintext or using the image-over-text style, is an example of how OCR-produced information might be used.
Moreover, the OCR SDK accepts input in the JPEG, GIF, PNG, PNM, and BMP formats, the TIFF format, and all its compression techniques. So the OCR will process your image, whether it originated from a scanner, the internet, or your camera.
Are There Limitations of OCR SDKs?
OCR is used to extract text information from photographs and classify it using reasoning. However, even OCR SDK has several restrictions, such as:
- OCR may incorrectly scan tilted text and misread handwritten fonts. This may prevent document transaction processing from finding particular words or phrases.
- Some OCR SDKs may be unable to decipher text found in images. They frequently only partially comprehend graphic text and do not fully transform the image data into text.
- Few OCR software may have increased error rates and widespread spelling issues.
What Are The Most Common OCR SDKs?
OCR SDKs translate text from handwritten papers so that machines can understand them. For example, the finance, accounting, legal, academic, and real estate industries frequently use OCR SDKs for various purposes.
These include data entry, information processing, and transcribing legal documents like affidavits, rulings, and filings.
Moreover, OCR SDKs extract data from tax records and electronically process invoices, receipts, bills of lading, and other documents.
Also, SDKs provide various APIs for scanning documents, categorizing content from multiple documents, and scanning survey forms.
The most popular OCR SDKs in the industry are:
- Filestack OCRs
- Google Cloud Vision
- Microsoft Computer Vision
- ABBY FineReader
Filestack’s OCR SDK is known for providing data capture services that can help businesses save time and improve the content workflow process.
Besides, it allows you to detect text in images and create searchable documents in a readable format. Moreover, it improves blurry documents and derives high-quality extractions that can improve workplace efficiency.
Moreover, this OCR suite provides access to several frameworks and programming languages, allowing you to choose and customize the software according to your needs.
Can You Improve Your Content Workflow Process?
Filestack’s OCR SDK is accurate, practical, and flexible. Thus, it helps you recognize printed text characters or image characteristics and transform those characters into unique identifying codes.
Finally, this tool can digitize and extract data; from credit cards, passports, driver’s licenses, and tax receipts with just a few clicks. Therefore, you don’t have to arrange and simplify the data capturing process.
