PowerOCR™

OCR Solution

What is OCR?

Optical Character Recognition (OCR) is a cutting-edge technology that transforms unstructured data—including text, images, and handwriting—into structured formats that machines can easily interpret and manipulate.
For instance, when you scan or upload an image of an invoice using OCR, the system accurately converts the visual information into editable text. This allows for streamlined processing and management of the data on your computer, facilitating tasks such as invoicing, record-keeping, and data entry. Below is an example of OCR input and output:

What is our OCR Solution?

Our OCR engine operates primarily as a web-based service, seamlessly integrating with clients' existing systems. It functions as a powerful scanner, transforming both paper documents and digital images into machine-readable and editable formats. This OCR engine follows a systematic process:

Image acquisition

The OCR engine scans all incoming documents, converting them into a digital format. During this phase, it analyzes the document to distinguish between light and dark areas, classifying the dark areas as text and the light areas as background.

Preprocessing

In order to effectively read text, the OCR engine undergoes a thorough preprocessing phase to enhance image quality and accuracy. This involves several key techniques: deskewing, which corrects any misalignment from the scanning process; despeckling, where unwanted digital artifacts and noise are eliminated to create smoother text edges; and the removal of graphic elements such as boxes and lines that may interfere with text recognition. Additionally, the OCR engine employs advanced script recognition capabilities to support multiple languages, ensuring that the digital image is clean and optimized for accurate character recognition.

Text recognition

The OCR engine employs two primary algorithms—pattern matching and feature extraction—to accurately identify text within the darker areas of an image. This process targets characters, including symbols, digits, and alphabetic letters, ensuring precise recognition and classification.

Pattern Matching

Pattern matching and pattern recognition are essential techniques in OCR, enabling the identification of characters by isolating specific images known as glyphs and comparing them to stored versions. This process relies on the similarity of font and scale between the input and stored glyphs, making it particularly effective for scanned documents typed in familiar fonts. However, successful recognition depends on the characters being in a font that the OCR has been trained to identify. With the vast array of fonts and languages—such as Arabic, Chinese, English, French, German, Greek, Japanese, Korean, and Spanish—training an OCR system to accommodate every possible combination poses significant challenges and demands extensive resources.

Feature recognition

Feature extraction involves analyzing glyphs by decomposing them into fundamental attributes like lines, closed loops, line direction, and intersections. It subsequently evaluates a font that it hasn't encountered before. OCR employs specific rules related to these attributes to identify letters and numbers in a scanned document. Key features considered include the count of angled lines, intersections, and any loops or curves present in a character. Once a character is recognized, it is transformed into an American Standard Code for Information Interchange (ASCII) code, which computer systems utilize for further processing.

Layout recognition

It is an advanced OCR technology that examines the structure of a document image. It segments the page into various components, including blocks of text, tables, and images. The lines of text are further broken down into words and then into individual characters. Once the characters are isolated, the program compares them against a library of pattern images. After evaluating all possible matches, it produces the recognized text.

Postprocessing

Once the information is collected and stored in a file, the OCR system generates two versions of the original document: one in its original state and another in an editable format or PDF. This dual output enhances document management by providing easy access to both the scanned version and the editable text.

How does this work?

1

OCR  can extract text from images, save it as a text file, and support various formats, including jpg, jpeg, png, bmp, tiff, and pdf.

2

The initial phase of the OCR process involves image acquisition, where a scanner captures text from a physical document and transforms it into a black-and-white image.

3

Following this, the image is refined by eliminating digital artifacts such as spots, boxes, and lines, and by aligning the text properly.

4

Once the OCR engine recognizes the characters, it translates the data into a digital file that can be easily shared, searched, edited, and copied.

5

There are various methods to enhance the output from the OCR process, such as utilizing a computer dictionary to correct nonsensical words, similar to the auto-correct feature found on many devices.

6

One of the most common applications of OCR is the conversion of printed documents into machine-readable text. After a paper document is scanned and processed through OCR, its text can be edited using word processors like Microsoft Word or Google Docs. This technology can significantly improve efficiency across various sectors, including education, finance, healthcare, logistics, and transportation, by facilitating the processing and retrieval of loan documents, patient records, insurance forms, labels, invoices, and receipts.

With this kind of OCR technology text recognition, scanned documents can be integrated into big-data systems capable of reading client information from bank statements, contracts, and other crucial printed materials. Instead of requiring employees to sift through numerous image documents and manually input data into an automated big-data processing workflow, organizations can leverage OCR to streamline this process at the data input stage.

The value of our OCR Solution

Our OCR solution offers exceptional value to your document management process. Here’s how:

Versatility Across Document Types

  • Printed Text: Easily convert printed documents into editable formats.
  • Handwriting: Accurately recognize and digitize handwritten notes and forms.
  • Form Recognition: Effortlessly extract data from structured forms, saving you time and effort.
  • Hybrid Text and Image: Process documents featuring both text and images, ensuring no information is overlooked.

Speed and Efficiency

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Accuracy and Reliability

Advanced algorithms provide high accuracy identification, minimizing the need for manual corrections and boosting productivity.

Cost-Effective

By streamlining the OCR workflows, our solution saves you both time and money, allowing you to focus on what truly matters.

Use scenarios for different industries

Healthcare

Streamline patient records and prescriptions, enhancing both efficiency and accuracy. By digitizing medical documents, healthcare professionals can quickly access patient histories, reduce administrative burdens, and improve patient care outcomes.

Finance

Automate data entry from invoices, receipts, and forms, significantly reducing errors and saving valuable time. This allows finance teams to focus on strategic tasks and enhances financial reporting accuracy.

Legal

Enhance the management of contracts and case documents through rapid retrieval and in-depth analysis. By utilizing OCR technology, legal professionals can quickly locate relevant information, facilitating more efficient case preparation and decision-making.

Education

Convert handwritten notes and forms into digital formats, improving accessibility and organization. This transformation not only aids in preserving valuable information but also supports students and educators in managing their resources effectively.

Retail

Optimize inventory management by digitizing receipts and product information. This results in more accurate stock tracking, timely reordering, and enhanced customer service, ultimately driving sales and profitability.

Insurance

Expedite claims processing by accurately extracting data from various documents. This leads to faster response times for clients, improved customer satisfaction, and streamlined operations within insurance firms.