We have developed a solution for automatic text extraction using computer vision, text recognition, ocr, machine learning and deep learning technologies. User interface or batch process to scan images and digital documents, extract content and use it for further processing with third-party systems such as ERP, accounting and RPA..Such solutions can be integrated into existing workflows for fast processing, subject to approval or review. Its automated nature allows for the customization of additional benefits such as rule-based notifications, alerts, reminders, and text translation to provide real-time information to users.
Document text extraction and processing systems are used in many industries, leading to workflow automation and process reengineering. The legal industry, which relies heavily on paper documents, can easily benefit from the simplicity and convenience of such innovative solutions. This solution helps improve the efficiency of organizations that process large amounts of documents. Each document has a different format, even if it is of the same type (such as an invoice). It is important that such a solution can handle these differences.
Ans - The use of technology to detect printed or handwritten text characters inside digital pictures of physical documents, such as scanned paper documents, is known as OCR (optical character recognition). OCR is a technology that examines a document's text and converts the characters into code that may be utilized for data processing. Text recognition is a term that is occasionally used to refer to OCR.
Ans - The physical form of a document is processed using a scanner in the first step of OCR. OCR software turns the document into a two-color, or black and white, version once all pages have been duplicated. The light and dark regions of the scanned-in picture or bitmap are identified as characters that need to be recognized, while the light areas are designated as background.
The dark patches are then analyzed further to determine if they contain alphabetic letters or numeric digits. OCR applications use a variety of techniques, but most focus on one character, phrase, or block of text at a time. After that, one of two algorithms is used to identify the characters:
OCR applications are fed samples of text in various fonts and formats, which are then used to compare and identify characters in the scanned document.
To recognize characters in a scanned document, OCR algorithms apply rules based on the attributes of a single letter or number. For comparison, features might include the number of angled lines, crossing lines, or curves in a character. For example, the capital letter "A" might be represented by two diagonal lines intersected by a horizontal line in the middle. When a character is detected, it is transformed into an ASCII code that computer systems may utilize to do additional operations.
Ans - OCR is a technology that examines a document's text and converts the characters into code that may be utilized for data processing. Text recognition is a term that is occasionally used to refer to OCR.