vDigiDocr (OCR)
AI-Powered OCR → to recognize printed or handwritten text characters inside digital images of physical documents, Such as
- scanned paper documents.
- Invoices data capture
- Creating machine-readable text from handwritten notes.
- Making electronic publications, such as Google Books or PDFs, searchable.
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.
For More Info :
VisitWhat we offer in vDigiDocr (OCR)
- Hybrid Solution - Standalone as well as Web Based.
- Document scanning/processing via UI as well as Batch Processing.
- Supports Template based and Machine Learning based workflows.
- Formats supported for incoming documents - pdf, doc, gif, tif, jpeg, etc.
- Formats supported for output - csv, json, xml, etc.
- Model Training on Cloud Platform.
- Scalable & High Accuracy Platform.
- Modular Service Oriented Architecture, Integration to 3rd party system like Accounting or RPA possible.
- Can be expanded to include support for hand-writen text and multiple languages.
Technology
- Tesseract, Computer Vision, OpenCV, Python, ReactJS, NodeJS, GPU Powered Google Cloud Platform Collab or AWS EC2 G3, Docker/Container
What Benefits you get by choosing our vDigiDocr (OCR)
- Improves Productivity
- Cost Reduction
- Highly Accuracy
- Speed
- Data Usability, Searchability & Conversion
- Data Security
- Improved Customer Service & Satisfaction
Our Clients
Few use cases where the vDigiDocr (OCR) solution can be used
- Data entry for business documents, e.g. Cheque, passport, invoice, bank statement and receipt.
- Automatic number plate recognition.
- In airports, for passport recognition and information extraction.
- Automatic insurance documents key information extraction.
- Traffic sign recognition
- Academic use for scanning of books, answer sheets, hand written notes, etc
Modes Of Operations
- Manual flow in which the documents are scanned via UI where the user marks the boundaries of the data to be retrieved from the document. To be used for ad hoc document processing with high accuracy.
- Semi-Automatic flow in which templates are pre-defined with the boundaries marked for the list of data fields to be retrieved from the document of specific format. Any document of that format will get auto-scanned via UI or batch process using the same template and the extracted Output will be displayed on the UI or saved into a db or csv file for further processing. To be used where images/documents of the same format to be processed repeatedly with high accuracy
- Automatic flow uses machine and deep learning algorithms to scan the documents via UI or batch process. It auto marks the boundaries of the data fields of interest and retrieves the data. It uses a model to auto mark the boundaries. Model is pre-trained with the relevant documents so that it can apply on any new document of any format. More the training, better is the accuracy of data extraction. Deep Learning Model runs on any Cloud platform like AWS or Google and is trained under supervision .Cloud platform is just required to train the model and generate the meta-data file which is bundled with the software and is used for processing at run-time. Cloud platform is not required at run-time so the auto workflow is quite fast, efficient and cost effective.
FAQ
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:
- 1. Pattern Recognition
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.
- 2. Feature detection:
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.